Cost Factor Focused Scheduling and Sequencing: A Neoteric Literature Review

  • Prasad Bari Department of Mechanical Engineering, Veermata Jijabai Technological Institute, Mumbai, India, Department of Mechanical Engineering, Fr. C. Rodrigues Institute of Technology, Vashi, Navi-Mumbai, India
  • Prasad Karande Department of Mechanical Engineering, Veermata Jijabai Technological Institute, Mumbai, India
Keywords: Scheduling, Sequencing, Cost, Literature review


The hastily emergent concern from researchers in the application of scheduling and sequencing has urged the necessity for analysis of the latest research growth to construct a new outline. This paper focuses on the literature on cost minimization as a primary aim in scheduling problems represented with less significance as a whole in the past literature reviews. The purpose of this paper is to have an intensive study to clarify the development of cost-based scheduling and sequencing (CSS) by reviewing the work published over several parameters for improving the understanding in this field. Various parameters, such as scheduling models, algorithms, industries, journals, publishers, publication year, authors, countries, constraints, objectives, uncertainties, computational time, and programming languages and optimization software packages are considered. In this research, the literature review of CSS is done for thirteen years (2010-2022). Although CSS research originated in manufacturing, it has been observed that CSS research publications also addressed case studies based on health, transportation, railway, airport, steel, textile, education, ship, petrochemical, inspection, and construction projects. A detailed evaluation of the literature is followed by significant information found in the study, literature analysis, gaps identification, constraints of work done, and opportunities in future research for the researchers and experts from the industries in CSS.


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Abadi, S. T. S., Tokmehdash, N. M., Hosny, A., Nik‐bakht, M. (2021). Bim‐based co‐simulation of fire and occupants’ behavior for safe construction rehabilitation planning. Fire, 4(4).

Abdullah, S., Shamayleh, A., Ndiaye, M. (2019). Three stage dynamic heuristic for multiple plants capacitated lot sizing with sequence-dependent transient costs. Computers and Industrial Engineering, 127, 1024–1036.

Abotaleb, I. S., El-adaway, I. H., Ibrahim, M. W., Hanna, A. S., Russell, J. S. (2020). Developing a Rating Score for Out-of-Sequence Construction. Journal of Management in Engineering, 36(3), 04020013.

Agnetis, A., Nicosia, G., Pacifici, A., Pferschy, U. (2015). Scheduling two agent task chains with a central selection mechanism. Journal of Scheduling, 18(3), 243–261. DOI:

Ait-Alla, A., Teucke, M., Lütjen, M., Beheshti-Kashi, S., Karimi, H. R. (2014). Robust production planning in fashion apparel industry under demand uncertainty via conditional value at risk. Mathematical Problems in Engineering, DOI:

Al-Refaie, A., Abedalqader, H. (2022). Optimal berth scheduling and sequencing under unexpected events. Journal of the Operational Research Society, 73(2), 430–444.

Al-Refaie, A., Judeh, M., Chen, T. (2018a). Optimal multiple-period scheduling and sequencing of operating room and intensive care unit. Operational Research, 18(3), 645–670. DOI:

Al-Refaie, A., Judeh, M., Li, M. H. (2018b). Optimal fuzzy scheduling and sequencing of multiple-period operating room. Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM, 32(1), 108–121. DOI:

Alaghebandha, M., Naderi, B., Mohammadi, M. (2019). Economic lot sizing and scheduling in distributed permutation flow shops. Journal of Optimization in Industrial Engineering, 12(1), 103–117.

Alfieri, A., Cantamessa, M. (2010). Optimising recipes in hybrid continuous-batch manufacturing systems: Application in the multi-layer plywood industry. International Journal of Production Research, 48(6), 1539–1556. DOI:

Ali, A., Iqbal, M. M. (2022). A cost and energy efficient task scheduling technique to offload microservices based applications in mobile cloud computing. IEEE Access, 10, 46633–46651.

Álvarez-Gil, N., Álvarez García, S., Rosillo, R., de la Fuente, D. (2022). Sequencing jobs with asymmetric costs and transition constraints in a finishing line: A real case study. Computers and Industrial Engineering, 165.

Ardakani, A., Fei, J., Beldar, P. (2020). Truck-to-door sequencing in multi-door cross-docking system with dock repeat truck holding pattern. International Journal of Industrial Engineering Computations, 11(2), 201–220.

Areal, J. J., Martín, R. M., Campos, J. G. (2011). Simulated annealing vs. genetic algorithms applied using a new cost function for the car sequencing problem. International Journal of Manufacturing Technology and Management, 23(1–2), 113–136. DOI:

Armstrong, M., Galli, A. (2012). New approach to flexible open pit optimisation and scheduling. Transactions of the Institutions of Mining and Metallurgy, Section A: Mining Technology, 121(3), 132–138. DOI:

Asad, M. W. A. (2011). A heuristic approach to long-range production planning of cement quarry operations. Production Planning and Control, 22(4), 353–364. DOI:

Azari-Rad, S., Yontef, A., Aleman, D. M., Urbach, D. R. (2014). A simulation model for perioperative process improvement. Operations Research for Health Care, 3(1), 22–30. DOI:

Baker, K. R. (2014). Minimizing earliness and tardiness costs in stochastic scheduling. European Journal of Operational Research, 236(2), 445–452. DOI:

Baker, K. R., Scudder, G. D. (1990). Sequencing with earliness and tardiness penalties. A review. Operations Research, 38(1), 22–36. DOI:

Baker, K. R., Trietsch, D. (2009). Principles of Sequencing and Scheduling. In Principles of Sequencing and Scheduling. DOI:

Ballester N., Parikh P. J., Kong N., Peck J. (2022). Sequencing daily patient workload for an ancillary service provider. IEEE Transactions on Automation Science and Engineering, 19(1), 178-190. doi: 10.1109/TASE.2019.2896317.

Bari, P., Karande, P. (2021). Application of PROMETHEE-GAIA method to priority sequencing rules in a dynamic job shop for single machine. Materials Today: Proceedings, 46(17), 7258-7264

Barlatt, A. Y., Cohn, A. M., Gusikhin, O. (2010). A hybridization of mathematical programming and dominance-driven enumeration for solving shift-selection and task-sequencing problems. Computers and Operations Research, 37(7), 1298–1307. DOI:

Bayu, F., Panda, D., Shaik, M. A., Ramteke, M. (2020). Scheduling of gasoline blending and distribution using graphical genetic algorithm. Computers and Chemical Engineering, 133, 106636.

Bhosale, K. C., Pawar, P. J. (2020). Production planning and scheduling problem of continuous parallel lines with demand uncertainty and different production capacities. Journal of Computational Design and Engineering, 7(6), 761–774.

Biele, A., Mönch, L. (2019). Decomposition methods for cost and tardiness reduction in aircraft manufacturing flow lines. Computers and Operations Research, 103, 134–147.

Boysen, N., Fliedner, M., Scholl, A. (2009). Sequencing mixed-model assembly lines: Survey, classification and model critique. European Journal of Operational Research, 192(2), 349–373. DOI:

Braat, J., Hamers, H., Klijn, F., Slikker, M. (2019). A selfish allocation heuristic in scheduling: Equilibrium and inefficiency bound analysis. European Journal of Operational Research, 273(2), 634–645.

Bueno, L., Magatão, L., Arruda, L. V. R., Neves, F., Monteiro, A., Vaqueiro, J. P. (2020). Assigning and sequencing batches and blends of oil derivatives in a mesh-like pipeline network. Computers and Chemical Engineering, 139, 106894.

Burger, A. P., Jacobs, C. G., van Vuuren, J. H., Visagie, S. E. (2015). Scheduling multi-colour print jobs with sequence-dependent setup times. Journal of Scheduling, 18(2), 131–145. DOI:

Cafaro, D. C., Cerdá, J. (2010). Operational scheduling of refined products pipeline networks with simultaneous batch injections. Computers and Chemical Engineering, 34(10), 1687–1704. DOI:

Campos, P. H. A., Cabral, I. E., Ortiz, C. E. A., Morales, N. (2018). Comparison between the application of the conventional mine planning and of the direct block scheduling on an open pit mine project. Revista Escola de Minas, 71(2), 269–274. DOI:

Canca, D., De-Los-Santos, A., Laporte, G., Mesa, J. A. (2019). The railway rapid transit network construction scheduling problem. Computers and Industrial Engineering, 138, 106075.

Carvalho, D. M., Nascimento, M. C. V. (2022). Hybrid metaheuristics to solve the integrated lot sizing and scheduling problem on parallel machines with sequence-dependent and non-triangular setup. European Journal of Operational Research, 296(1), 158–173.

Cayo, P., Onal, S. (2020). A shifting bottleneck procedure with multiple objectives in a complex manufacturing environment. Production Engineering, 14(2), 177–190.

Cerdá, J., Pautasso, P. C., Cafaro, D. C. (2015). Efficient approach for scheduling crude oil operations in marine- Access refineries. Industrial and Engineering Chemistry Research, 54(33), 8219–8238. DOI:

Çetinkaya, F. C., Duman, M. (2021). Scheduling with lot streaming in a two-machine re-entrant flow shop. Operational Research in Engineering Sciences: Theory and Applications, 4(3), 142–175. DOI:

Chaieb Memmi, I., Hammani Laaroussi, S. (2013). A new approach for solving capacitated lot sizing and scheduling problem with sequence and period-dependent setup costs. Journal of Industrial Engineering and Management, 6(4), 1027–1054. DOI:

Chan, F. T. S., Choy, K. L., Bibhushan. (2011). A genetic algorithm-based scheduler for multiproduct parallel machine sheet metal job shop. Expert Systems with Applications, 38(7), 8703–8715. DOI:

Chen, R. R., Robinson, L. W. (2014). Sequencing and scheduling appointments with potential call-in patients. Production and Operations Management, 23(9), 1522–1538. DOI:

Cheng, T. C. E. (1991). Optimal assignment of slack due-dates and sequencing of jobs with random processing times on a single machine. European Journal of Operational Research, 51(3), 348–353. DOI:

Choi, S., Wilhelm, W. E. (2020). Sequencing in an appointment system with deterministic arrivals and non-identical exponential service times. Computers and Operations Research, 117, 104901.

Choi, S., Wilhelm, W. E. (2012). An analysis of sequencing surgeries with durations that follow the lognormal, gamma, or normal distribution. IIE Transactions on Healthcare Systems Engineering, 2(2), 156–171. DOI:

Chou, F. N. F., Lee, H. C., Yeh, W. W. G. (2013). Effectiveness and Efficiency of Scheduling Regional Water Resources Projects. Water Resources Management, 27(3), 665–693. DOI:

Corry, P., Bierwirth, C. (2019). The berth allocation problem with channel restrictions. Transportation Science, 53(3), 708–727.

Costa, A., Fichera, S., Cappadonna, F. A. (2013). A genetic algorithm for scheduling both job families and skilled workforce. International Journal of Operations and Quantitative Management, 19(4), 221–247.

Cui, Y., Cao, K., Li, L., Zhou, J., Wei, T., Hu, S. (2020). Augmented Cross-Entropy-Based Joint Temperature Optimization of Real-Time 3-D MPSoC Systems. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39(10), 1987–1999.

Czibula, O. G., Gu, H., Hwang, F. J., Kovalyov, M. Y., Zinder, Y. (2016). Bi-criteria sequencing of courses and formation of classes for a bottleneck classroom. Computers and Operations Research, 65, 53–63. DOI:

Dang, Q. V., Singh, N., Adan, I., Martagan, T., van de Sande, D. (2021). Scheduling heterogeneous multi-load AGVs with battery constraints. Computers and Operations Research, 136, 105517.

De Maere, G., Atkin, J. A. D., Burke, E. K. (2018). Pruning rules for optimal runway sequencing. Transportation Science, 52(4), 898–916. DOI:

Deceuninck, M., Fiems, D., De Vuyst, S. (2018). Outpatient scheduling with unpunctual patients and no-shows. European Journal of Operational Research, 265(1), 195–207. DOI:

Djassemi, M., Seifoddini, H. (2019). Analysis of critical machine reliability in manufacturing cells. Journal of Industrial Engineering and Management, 12(1), 70–82.

Domínguez-Martín, B., Rodríguez-Martín, I., Salazar-González, J. J. (2017). An exact algorithm for a Vehicle-and-Driver Scheduling Problem. Computers and Operations Research, 81, 247–256. DOI:

Dou, J., Su, C., Zhao, X. (2020). Mixed integer programming models for concurrent configuration design and scheduling in a reconfigurable manufacturing system. Concurrent Engineering Research and Applications, 28(1), 32–46.

Durazo-Cardenas, I., Starr, A., Turner, C. J., Tiwari, A., Kirkwood, L., Bevilacqua, M., Tsourdos, A., Shehab, E., Baguley, P., Xu, Y., Emmanouilidis, C. (2018). An autonomous system for maintenance scheduling data-rich complex infrastructure: Fusing the railways’ condition, planning and cost. Transportation Research Part C: Emerging Technologies, 89, 234–253. DOI:

Eguia, I., Lozano, S., Racero, J., Guerrero, F. (2011). A methodological approach for designing and sequencing product families in Reconfigurable Disassembly Systems. Journal of Industrial Engineering and Management, 4(3), 418–435. DOI:

Elyasi, A., Salmasi, N. (2013). Due date assignment in single machine with stochastic processing times. International Journal of Production Research, 51(8), 2352–2362. DOI:

Eun, Y., Hwang, I., Bang, H. (2010). Optimal arrival flight sequencing and scheduling using discrete airborne delays. IEEE Transactions on Intelligent Transportation Systems, 11(2), 359–373. DOI:

Faghihi, V., Reinschmidt, K. F., Kang, J. H. (2014). Construction scheduling using Genetic Algorithm based on Building Information Model. Expert Systems with Applications, 41(16), 7565–7578. DOI:

Fang, K. T., Lin, B. M. T. (2013). Parallel-machine scheduling to minimize tardiness penalty and power cost. Computers and Industrial Engineering, 64(1), 224–234. DOI:

Farhadi, F., Ghoniem, A., Al-Salem, M. (2014). Runway capacity management - An empirical study with application to Doha International Airport. Transportation Research Part E: Logistics and Transportation Review, 68, 53–63. DOI:

Farmand, N., Zarei, H., Rasti-Barzoki, M. (2021). Two meta-heuristic algorithms for optimizing a multi-objective supply chain scheduling problem in an identical parallel machines environment. International Journal of Industrial Engineering Computations, 12(3), 249–272.

Feng, C. W., Chen, Y. J., Huang, J. R. (2010). Using the MD CAD model to develop the time-cost integrated schedule for construction projects. Automation in Construction, 19(3), 347–356. DOI:

Fernandez, S., Alvarez, S., Díaz, D., Iglesias, M., Ena, B. (2014). Scheduling a galvanizing line by ant colony optimization. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8667, 146–157. DOI:

Ferro, G., Laureri, F., Minciardi, R., Robba, M. (2019). A predictive discrete event approach for the optimal charging of electric vehicles in microgrids. Control Engineering Practice, 86, 11–23.

Fumero, Y., Corsano, G., Montagna, J. M. (2013). A Mixed Integer Linear Programming model for simultaneous design and scheduling of flowshop plants. Applied Mathematical Modelling, 37(4), 1652–1664. DOI:

Fumero, Y., Montagna, J. M., Corsano, G. (2012). Simultaneous design and scheduling of a semicontinuous/batch plant for ethanol and derivatives production. Computers and Chemical Engineering, 36(1), 342–357. DOI:

Gao, C., Qu, D. (2018). A modelling and a new hybrid MILP/CP decomposition method for parallel continuous galvanizing line scheduling problem. ISIJ International, 58(10), 1820–1827.

Gao, Z., Bard, J. F., Chacon, R., Stuber, J. (2015). An assignment-sequencing methodology for scheduling assembly and test operations with multi-pass requirements. IIE Transactions (Institute of Industrial Engineers), 47(2), 153–172. DOI:

Gao, Z., Sun, D., Zhao, R., Dong, Y. (2021). Ship-unloading scheduling optimization for a steel plant. Information Sciences, 544, 214–226.

Gholipour-Kanani, Y., Tavakkoli-Moghaddam, R., Khorrami, A. (2011). Solving a multi-criteria group scheduling problem for a cellular manufacturing system by scatter search. Journal of the Chinese Institute of Industrial Engineers, 28(3), 192–205. DOI:

Gifford, T., Opicka, T., Sinha, A., Brink, D. Vanden, Gifford, A., Randall, R. (2018). Dispatch optimization in bulk tanker transport operations. Interfaces, 48(5), 403–421.

Glazer, A., Hassin, R., Ravner, L. (2018). A strategic model of job arrivals to a single machine with earliness and tardiness penalties. IISE Transactions, 50(4), 265–278. DOI:

Golmakani, H. R., Namazi, A. (2012). Multiple-route job shop scheduling with fixed periodic and age-dependent preventive maintenance to minimize makespan. Journal of Quality in Maintenance Engineering, 18(1), 60–78. DOI:

Golmohammadi, D. (2013). A neural network decision-making model for job-shop scheduling. International Journal of Production Research, 51(17), 5142–5157. DOI:

Gordon, V., Proth, J. M., Chu, C. (2002). A survey of the state-of-the-art of common due date assignment and scheduling research. European Journal of Operational Research, 139(1), 1–25. DOI:

Grabenstetter, D. H., Usher, J. M. (2015). Sequencing jobs in an engineer-to-order engineering environment. Production and Manufacturing Research, 3(1), 201–217. DOI:

Grigoriev, A., Kreuzen, V. J., Oosterwijk, T. (2021). Cyclic lot-sizing problems with sequencing costs. Journal of Scheduling, 24(2), 123–135.

Gu, H., Li, X., Lu, Z. (2021). Scheduling Spark Tasks with Data Skew and Deadline Constraints. IEEE Access, 9, 2793–2804.

Gul, S., Denton, B. T., Fowler, J. W., Huschka, T. (2011). Bi-criteria scheduling of surgical services for an outpatient procedure center. Production and Operations Management, 20(3), 406–417. DOI:

Gürel, S., Körpeoǧlu, E., Aktürk, M. S. (2010). An anticipative scheduling approach with controllable processing times. Computers and Operations Research, 37(6), 1002–1013. DOI:

Guzman, E., Andres, B., Poler, R. (2022). Matheuristic Algorithm for Job-Shop Scheduling Problem Using a Disjunctive Mathematical Model. Computers, 11(1), 1–16.

Haddad, A., Taajobian, M., Jahanian, A. (2018). Massive parallel digital microuidic biochip architecture for automating large-scale biochemistry assays. Scientia Iranica, 25(6D), 3461–3474.

Haoran, Z., Yongtu, L., Qi, L., Yun, S., Xiaohan, Y. (2018). A self-learning approach for optimal detailed scheduling of multi-product pipeline. Journal of Computational and Applied Mathematics, 327, 41–63. DOI:

Heath, S. K., Bard, J. F., Morrice, D. J. (2013). A GRASP for simultaneously assigning and sequencing product families on flexible assembly lines. Annals of Operations Research, 203(1), 295–323. DOI:

Ho, T. Y., Zengt, J., Chakrabarty, K. (2010). Digital microfluidic biochips: A vision for functional diversity and more than Moore. IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD, 578–585. DOI:

Hu, X., Wang, J., Leng, K. (2019). The Interaction between Critical Chain Sequencing, Buffer Sizing, and Reactive Actions in a CC/BM Framework. Asia-Pacific Journal of Operational Research, 36(3), 1–22.

Huang, J. Y., Yao, M. J. (2013). On the optimal lot-sizing and scheduling problem in serial-type supply chain system using a time-varying lot-sizing policy. International Journal of Production Research, 51(3), 735–750. DOI:

Hussain, M., Wei, L. F., Lakhan, A., Wali, S., Ali, S., Hussain, A. (2021). Energy and performance-efficient task scheduling in heterogeneous virtualized cloud computing. Sustainable Computing: Informatics and Systems, 30, 100517.

Hussain, M., Wei, L.-F., Rehman, A., Abbas, F., Hussain, A., Ali, M. (2022). Deadline-constrained energy-aware workflow scheduling in geographically distributed cloud data centers. Future Generation Computer Systems, 132, 211-222,

Jafarnia-Jahromi, M., Jain, R. (2020). Non-indexability of the stochastic appointment scheduling problem. Automatica, 118, 109016.

Kim, B., Youn, C. H., Park, Y. S., Lee, Y., Choi, W. (2012). An adaptive workflow scheduling scheme based on an estimated data processing rate for next generation sequencing in cloud computing. Journal of Information Processing Systems, 8(4), 555–566. DOI:

Kobayashi, M. (2021). Application of the surrogate gradient method for a multi-item single-machine dynamic lot size scheduling problem. SN Applied Sciences, 3(7).

Kong, W., Lei, Y., Ma, J. (2016). Virtual machine resource scheduling algorithm for cloud computing based on auction mechanism. Optik, 127(12), 5099–5104. DOI:

Kopanos, G. M., Puigjaner, L., Georgiadis, M. C. (2011). Production Scheduling in Multiproduct Multistage Semicontinuous Food Processes. Industrial and Engineering Chemistry Research, 50(10), 6316–6324. DOI:

Kurniawan, B., Chandramitasari, W., Gozali, A. A., Weng, W., Fujimura, S. (2020a). Triple-chromosome genetic algorithm for unrelated parallel machine scheduling under time-of-use tariffs. IEEJ Transactions on Electrical and Electronic Engineering, 15(2), 208–217.

Kurniawan, B., Song, W., Weng, W., Fujimura, S. (2020b). Distributed-elite local search based on a genetic algorithm for bi-objective job-shop scheduling under time-of-use tariffs. Evolutionary Intelligence, 0123456789.

Laili, Y., Peng, C., Chen, Z., Ye, F., Zhang, L. (2022). Concurrent local search for process planning and scheduling in the industrial Internet-of-Things environment. Journal of Industrial Information Integration, 28,

Lakhan, A., Mastoi, Q. U. A., Elhoseny, M., Memon, M. S., Mohammed, M. A. (2021a). Deep neural network-based application partitioning and scheduling for hospitals and medical enterprises using IoT assisted mobile fog cloud. Enterprise Information Systems, 16(7), 1–23.

Lakhan, A., Memon, M. S., Mastoi, Q., Elhoseny, M., Mohammed, M. A., Qabulio, M., Abdel-Basset, M. (2021b). Cost-efficient mobility offloading and task scheduling for microservices IoVT applications in container-based fog cloud network. Cluster Computing, 26,6429-6442.

Lakhan, A., Mohammed, M. A., Elhoseny, M., Alshehri, M. D., Abdulkareem, K. H., (2022a). Blockchain multi-objective optimization approach-enabled secure and cost-efficient scheduling for the Internet of Medical Things (IoMT) in fog-cloud system. Soft Computing. 26, 6429–6442.

Lakhan A., Mohammed M.A., Rashid A.N., Kadry S., Hameed A. K., Nedoma J., Martinek R., Razzak I. (2022b). Restricted Boltzmann machine assisted secure serverless edge system for internet of medical things. IEEE Journal of Biomedical and Health Informatics. doi: 10.1109/JBHI.2022.3178660.

Lauff, V., Werner, F. (2004). Scheduling with common due date, earliness and tardiness penalties for multimachine problems: A survey. Mathematical and Computer Modelling, 40(5–6), 637–655. DOI:

Le, C. V., Pang, C. K. (2013). Fast reactive scheduling to minimize tardiness penalty and energy cost under power consumption uncertainties. Computers and Industrial Engineering, 66(2), 406–417. DOI:

Lemos, R. F., Ronconi, D. P. (2015). Heuristics for the stochastic single-machine problem with E/T costs. International Journal of Production Economics, 168, 131–142. DOI:

Leyvand, Y., Shabtay, D., Steiner, G. (2010). Optimal delivery time quotation to minimize total tardiness penalties with controllable processing times. IIE Transactions (Institute of Industrial Engineers), 42(3), 221–231. DOI:

Li, D., Li, M., Meng, X., Tian, Y. (2015). A hyperheuristic approach for intercell scheduling with single processing machines and batch processing machines. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 45(2), 315–325. DOI:

Liang, F., Guo, Y., Fung, R. Y. K. (2015). Simulation-Based Optimization for Surgery Scheduling in Operation Theatre Management Using Response Surface Method. Journal of Medical Systems, 39(11). DOI:

Lin, D. Y., Chu, Y. M. (2013). The mixed-product assembly line sequencing problem of a door-lock company in Taiwan. Computers and Industrial Engineering, 64(1), 492–499. DOI:

Liu, X., Chen, J., Huang, X., Guo, S., Zhang, S., Chen, M. (2021). A new job shop scheduling method for remanufacturing systems using extended artificial bee colony algorithm. IEEE Access, 9, 132429–132441.

Liu, Z., Lu, L., Qi, X. (2018). Cost allocation in rescheduling with machine unavailable period. European Journal of Operational Research, 266(1), 16–28. DOI:

Lopes, T. C., Michels, A. S., Sikora, C. G. S., Molina, R. G., Magatão, L. (2018). Balancing and cyclically sequencing synchronous, asynchronous, and hybrid unpaced assembly lines. International Journal of Production Economics, 203, 216–224.

Lopes, T. C., Sikora, C. G. S., Michels, A. S., Magatão, L. (2020). An iterative decomposition for asynchronous mixed-model assembly lines: combining balancing, sequencing, and buffer allocation. International Journal of Production Research, 58(2), 615–630.

Lu, L., Liu, Z., Qi, X. (2013). Coordinated price quotation and production scheduling for uncertain order inquiries. IIE Transactions (Institute of Industrial Engineers), 45(12), 1293–1308. DOI:

Mak, H.-Y., Rong, Y., Zhang, J. (2013). Appointment scheduling with limited distributional information. Management Science, 61, 316-334. DOI:

Mancilla, C., Storer, R. (2012). A sample average approximation approach to stochastic appointment sequencing and scheduling. IIE Transactions (Institute of Industrial Engineers), 44(8), 655–670. DOI:

Mancilla, C., Storer, R. H. (2013). Stochastic sequencing of surgeries for a single surgeon operating in parallel operating rooms. IIE Transactions on Healthcare Systems Engineering, 3(2), 127–138. DOI:

Mandelbaum, A., Momčilović, P., Trichakis, N., Kadish, S., Leib, R., Bunnell, C. A. (2020). Data-driven appointment-scheduling under uncertainty: The case of an infusion unit in a cancer center. Management Science, 66(1), 243–270.

Martínez, K. P., Adulyasak, Y., Jans, R., Morabito, R., Toso, E. A. V. (2019). An exact optimization approach for an integrated process configuration, lot-sizing, and scheduling problem. Computers and Operations Research, 103, 310–323.

Martínez, K. P., Morabito, R., Toso, E. A. V. (2018). A coupled process configuration, lot-sizing and scheduling model for production planning in the molded pulp industry. International Journal of Production Economics, 204, 227–243.

Mathur, K., Süer, G. A. (2013). Math modeling and GA approach to simultaneously make overtime decisions, load cells and sequence products. Computers and Industrial Engineering, 66(3), 614–624. DOI:

Mazdeh, M. M., Zaerpour, F., Jahantigh, F. F. (2010a). A fuzzy modeling for single machine scheduling problem with deteriorating jobs. International Journal of Industrial Engineering Computations, 1(2), 147–156. DOI:

Mazdeh, M. M., Zaerpour, F., Zareei, A., Hajinezhad, A. (2010b). Parallel machines scheduling to minimize job tardiness and machine deteriorating cost with deteriorating jobs. Applied Mathematical Modelling, 34(6), 1498–1510. DOI:

Mendonça, N. D. P., Leite, I., Gomes, V. D. S., Andrade, M. F., Cruz, B. R., Silva, C. S. J., Gomide, L. R. (2022). Silvicultural tasks scheduling optimization: a case study of functions and methods. Revista Árvore. 46."

Mobaieen, S., Rabii, A., Mohamady, B. (2012). Optimal robot arm movement using tabu search algorithm. Research Journal of Applied Sciences, Engineering and Technology, 4(4), 383–386.

Mohan, S., Kumar, K. P. (2016). Waste Load Allocation Using Machine Scheduling: Model Application. Environmental Processes, 3(1), 139–151. DOI:

Mohtashami, A. (2015). A novel dynamic genetic algorithm-based method for vehicle scheduling in cross docking systems with frequent unloading operation. Computers and Industrial Engineering, 90, 221–240. DOI:

Mokhtari, H., Abadi, I. N. K., Cheraghalikhani, A. (2011). A multi-objective flow shop scheduling with resource-dependent processing times: Trade-off between makespan and cost of resources. International Journal of Production Research, 49(19), 5851–5875. DOI:

Molina-Sánchez, L. P., González-Neira, E. M. (2016). GRASP to minimize total weighted tardiness in a permutation flow shop environment. International Journal of Industrial Engineering Computations, 7(1), 161–176. DOI:

Mostafaei, H., Castro, P. M., Ghaffari-Hadigheh, A. (2015). A Novel monolithic MILP framework for lot-sizing and scheduling of multiproduct treelike pipeline networks. Industrial and Engineering Chemistry Research, 54(37), 9202–9221. DOI:

Murça, M. C. R. (2017). A robust optimization approach for airport departure metering under uncertain taxi-out time predictions. Aerospace Science and Technology, 68, 269–277. DOI:

Murugesan, G., Chellappan, C. (2012). Fuzzy based optimal allocation of resources for grid scheduling. Research Journal of Applied Sciences, 7(2), 119–125. DOI:

Musavi, M. M., Bozorgi-Amiri, A. (2017). A multi-objective sustainable hub location-scheduling problem for perishable food supply chain. Computers and Industrial Engineering, 113, 766–778. DOI:

Nazif, H. (2018). Operating room surgery scheduling with fuzzy surgery durations using a metaheuristic approach. advances in operations research, 1-8.

Nguyen, S., Zhang, M., Johnston, M., Tan, K. C. (2015). Automatic programming via iterated local search for dynamic job shop scheduling. IEEE Transactions on Cybernetics, 45(1), 1–14. DOI:

Nonsiri, S., Christophe, F., Coataneéa, E., Mokammel, F. (2014). A combined design structure matrix (DSM) and discrete differential evolution (DDE) approach for scheduling and organizing system development tasks modelled using SysML. Journal of Integrated Design and Process Science, 18(3), 19–40.

Oyetunji, E. O. (2009). Some common performance measures in scheduling problems: Review article. Research Journal of Applied Sciences, Engineering and Technology, 1(2), 6–9.

Paik, S., Lee, S., Shin, Y. (2011). Retiming pulsed-latch circuits with regulating pulse width. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 30(8), 1114–1127. DOI:

Palaniappan, P. K., Jawahar, N. (2010). Integration of procurement and production scheduling in flexible flow-line assembly. International Journal of Integrated Supply Management, 5(4), 344–364. DOI:

Pan, X., Geng, N., Xie, X. (2021). European Journal of Operational Research, 295(1), 246–260.

Pang, B., Xie, X., Ju, F., Pipe, J. (2022). A dynamic sequential decision-making model on MRI real-time scheduling with simulation-based optimization. Health Care Management Science, 25, 426-440.

Paul, S. K., Azeem, A. (2010). Minimization of work-in-process inventory in hybrid flow shop scheduling using fuzzy logic. International Journal of Industrial Engineering: Theory Applications and Practice, 17(2), 115–127.

Pautasso, P. C., Cafaro, D. C., Cerdá, J. (2019). Scheduling upstream operations at inland petroleum refineries using a precedence-based formulation. Industrial and Engineering Chemistry Research, 58(12), 4906–4924.

Pei, J., Wang, X., Fan, W., Pardalos, P. M., Liu, X. (2019). Scheduling step-deteriorating jobs on bounded parallel-batching machines to maximise the total net revenue. Journal of the Operational Research Society, 70(10), 1830–1847. DOI:

Pinedo, M. L. (2004). Planning and Scheduling in Manufacturing and Services. Springer Series in Operations Research and Financial Engineering.

Purohit, B. S., Lad, B. K. (2016). Production and maintenance planning: an integrated approach under uncertainties. International Journal of Advanced Manufacturing Technology, 86(9–12), 3179–3191. DOI:

Quinteros, M., Guignard, M., Weintraub, A., Llambias, M., Tapia, C. (2019). Optimizing the pipeline planning system at the national oil company. European Journal of Operational Research, 277(2), 727–739.

Ramezanian, R., Saidi-Mehrabad, M. (2012). Capacitated production planning problem considering the detailed scheduling constraints in a flow shop environment. International Journal of Management Science and Engineering Management, 7(4), 293–302.

Reddy, N. S., Lalitha, M. P., Pandey, S. P., Venkatesh, G. S. (2021). Simultaneous scheduling of machines and tools in a multi machine FMS with alternative routing using symbiotic organisms search algorithm. Journal of Engineering Research, 10,274-297,

Reddy, N. S., Ramamurthy V. D., Rao P. K. and Lalitha M. P. (2019). Integrated scheduling of machines, AGVs and tools in multi-machine FMS using crow search algorithm, International Journal of Computer Integrated Manufacturing, 32(11), 1117–1133.

Rezaeiahari, M., Khasawneh, M. T. (2020). Simulation optimization approach for patient scheduling at destination medical centers. Expert Systems with Applications, 140, 112881.

Rijal A., Bijvank M., Goel A., Koster R. (2021). Workforce scheduling with order-picking assignments in distribution facilities. Transportation Science, 55(3), 725-746.

Rodríguez-Sanz, Á., Cózar, P. L., Pérez-Castán, J. A., Comendador, F. G. (2021). Tactical runway scheduling for demand and delay management. IOP Conference Series: Materials Science and Engineering, 1024(1).

Rohaninejad, Mohamad, Kheirkhah, A., Fattahi, P., Vahedi-Nouri, B. (2015). A hybrid multi-objective genetic algorithm based on the ELECTRE method for a capacitated flexible job shop scheduling problem. International Journal of Advanced Manufacturing Technology, 77(1–4), 51–66. DOI:

Rohaninejad, Mohammad, Sahraeian, R., Nouri, B. V. (2016). Multi-objective optimization of integrated lot-sizing and scheduling problem in flexible job shops. RAIRO - Operations Research, 50(3), 587–609. DOI:

Roshanaei, V., Luong, C., Aleman, D. M., Urbach, D. R. (2017). Collaborative operating room planning and scheduling. INFORMS Journal on Computing, 29(3), 558–580. DOI:

Rudek, R. (2016). Computational complexity and solution algorithms for a vector sequencing problem. Computers and Industrial Engineering, 98, 384–400. DOI:

Saadouli, H., Jerbi, B., Dammak, A., Masmoudi, L., Bouaziz, A. (2015). A stochastic optimization and simulation approach for scheduling operating rooms and recovery beds in an orthopedic surgery department. Computers and Industrial Engineering, 80, 72–79. DOI:

Sadhasivam, N., Balamurugan, R., Pandi, M. (2018). Cancer diagnosis epigenomics scientific workflow scheduling in the cloud computing environment using an improved PSO algorithm. Asian Pacific Journal of Cancer Prevention, 19(1), 243–246.

Said, R., Elarbi, M., Bechikh, S., Said, L.B. (2021). Solving combinatorial bi-level optimization problems using multiple populations and migration schemes. Operational Research, 22, 1697–1735.

Samorani, M., Ganguly, S. (2016). Optimal sequencing of unpunctual patients in high-service-level clinics. Production and Operations Management, 25(2), 330–346. DOI:

Santos, M. O., Almada-Lobo, B. (2012). Integrated pulp and paper mill planning and scheduling. Computers and Industrial Engineering, 63(1), 1–12. DOI:

Savino, M. M., Meoli, E., Luo, M., Wong, M. M. (2010). Dynamic batch scheduling in a continuous cycle-constrained production system. International Journal of Services Operations and Informatics, 5(4), 313–329. DOI:

Seif, J., Yu, A. J., Rahmanniyay, F. (2018). Modelling and optimization of a bi-objective flow shop scheduling with diverse maintenance requirements. International Journal of Production Research, 56(9), 3204–3225. DOI:

Senturk, I. F., Balakrishnan, P., Abu-Doleh, A., Kaya, K., Malluhi, Q., Çatalyürek, Ü. V. (2018). A resource provisioning framework for bioinformatics applications in multi-cloud environments. Future Generation Computer Systems, 78, 379–391. DOI:

Shahram F. S., Vahdani, B. (2019). Assignment and scheduling trucks in cross-docking system with energy consumption consideration and trucks queuing. Journal of Cleaner Production, 213, 21–41.

Shehadeh, K. S., Padman, R. (2022). Stochastic optimization approaches for elective surgery scheduling with downstream capacity constraints: Models, challenges, and opportunities. Computers and Operations Research, 137, 105523.

Shen, K., De Pessemier, T., Martens, L., Joseph, W. (2021). A parallel genetic algorithm for multi-objective flexible flowshop scheduling in pasta manufacturing. Computers and Industrial Engineering, 161, 107659.

Shobaki, G., Gordon, V. S., McHugh, P., Dubois, T., Kerbow, A. (2022). Register-Pressure-Aware instruction scheduling using ant colony optimization. ACM Transactions on Architecture and Code Optimization, 19(2), 1–23.

Sidney, J. B. (1977). Optimal Single-Machine Scheduling with Earliness and Tardiness Penalties. Operations Research, 25(1), 62–69. DOI:

Singh, J., Cheng Jack C. P., Anumba Chimay J. (2021). BIM-Based approach for automatic pipe systems installation coordination and schedule optimization. Journal of Construction Engineering and Management, 147.

Sinisterra, W. Q., Cavalcante, C. A. V. (2020). An integrated model of production scheduling and inspection planning for resumable jobs. International Journal of Production Economics, 227.

Stanković, A., Petrović, G., Ćojbašić, Ž., Marković, D. (2020). An application of metaheuristic optimization algorithms for solving the flexible job-shop scheduling problem. Operational Research in Engineering Sciences: Theory and Applications, 3(3), 13–28. DOI:

Stiverson, P., Rathinam, S. (2011). Heuristics for a runway-queue management problem. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 225(5), 481–499. DOI:

Su, Y., Chu, X., Zhang, Z., Chen, D. (2015). Process planning optimization on turning machine tool using a hybrid genetic algorithm with local search approach. Advances in Mechanical Engineering, 7(4), 1–14. DOI:

Subbiah, S., Schoppmeyer, C., Engell, S. (2011). An intuitive and efficient approach to process scheduling with sequence-dependent changeovers using timed automata models. Industrial and Engineering Chemistry Research, 50(9), 5131–5152. DOI:

Sun, X., Garg, M., Balaporia, Z., Bailey, K., Gifford, T. (2014). Optimizing transportation by inventory routing and workload balancing: Optimizing daily dray operations across an intermodal freight network. Interfaces, 44(6), 579–590. DOI:

Sun, Y., Raghavan, U. N., Vaze, V., Hall, C. S., Doyle, P., Richard, S. S., Wald, C. (2021). Stochastic programming for outpatient scheduling with flexible inpatient exam accommodation. Health Care Management Science, 24(3), 460–481.

Supithak, W., Liman, S. D., Montes, E. J. (2010). Lot-sizing and scheduling problem with earliness tardiness and setup penalties. Computers and Industrial Engineering, 58(3), 363–372. DOI:

T’Kindt, V., Billaut, J.-C. (2005). Multicriteria Scheduling - Theory, Models and Algorithms. Springer-Verlag.

Tan, X. (2012). A mathematical quadratic integer model based on ant colony optimization for air traffic control. International Journal on Advances in Information Sciences and Service Sciences, 4(1), 185-191.

Tang, Q., Li, J., Floudas, C. A., Deng, M., Yan, Y., Xi, Z., Chen, P., Kong, J. (2012). Optimization framework for process scheduling of operation-dependent automobile assembly lines. Optimization Letters, 6(4), 797–824. DOI:

Tavakkoli-Moghaddam, R., Yaghoubi-Panah, M., Radmehr, F. (2012). Scheduling the sequence of aircraft landings for a single runway using a fuzzy programming approach. Journal of Air Transport Management, 25, 15–18. DOI:

Toledo, M.C.F., De Oliveira, L., Pereira, R.D.F., França, P.M., Morabito, R. (2014). A genetic algorithm/mathematical programming approach to solve a two-level soft drink production problem. Computers and Operations Research, 48, 40–52. DOI:

Transchel, S., Minner, S., Kallrath, J., Lohndorf, N., Eberhard, U. (2011). A hybrid general lot-sizing and scheduling formulation for a production process with a two-stage product structure. International Journal of Production Research, 49(9), 2463–2480. DOI:

Tsai, S. C., Yeh, Y., Kuo, C. Y. (2021). Efficient optimization algorithms for surgical scheduling under uncertainty. European Journal of Operational Research, 293(2), 579–593.

Udhayakumar, P., Kumanan, S. (2010). Sequencing and scheduling of job and tool in a flexible manufacturing system using ant colony optimization algorithm. International Journal of Advanced Manufacturing Technology, 50(9–12), 1075–1084. DOI:

Vandenberghe, M., Vuyst, S. De, Aghezzaf, E. H., Bruneel, H. (2020). Stochastic surgery selection and sequencing under dynamic emergency break-ins. Journal of the Operational Research Society, 72(6), 1–21.

Wah-Peng L., See-Seng N., Tien-Choon T., Cheng-Sim L., Jeffrey Y.B.-H. (2017). Critical factors affecting productivity for table form system in the Malaysian construction industry. Advanced Science Letters, 23(7). DOI:

Wang, C., Gong, L., Li, X., Zhou, X. (2020). A ubiquitous machine learning accelerator with automatic parallelization on FPGA. IEEE Transactions on Parallel and Distributed Systems, 31(10), 2346–2359.

Wang, C., Mao, Y. sheng, Hu, B., Deng, Z., Shin, J. G. (2016). Ship block transportation scheduling problem based on greedy algorithm. Journal of Engineering Science and Technology Review, 9(2), 93–98.

Wang, C. N., Hsu, H. P., Fu, H. P., Phan, N. K. P., Nguyen, V. T. (2022). Scheduling flexible flow shop in labeling companies to minimize the makespan. Computer Systems Science and Engineering, 40(1), 17–36.

Wang, D. J., Liu, F., Jin, Y. (2019). A proactive scheduling approach to steel rolling process with stochastic machine breakdown. Natural Computing, 18(4), 679–694. DOI:

Wang, J., Cabrera, J., Tsui, K. L., Guo, H., Bakker, M., Kostis, J. B. (2020). Clinical and nonclinical effects on operative duration: Evidence from a database on thoracic surgery. Journal of Healthcare Engineering, 2020.

Wang, J. B., Zhang, B., Li, L., Bai, D., Feng, Y. B. (2020). Due-window assignment scheduling problems with position-dependent weights on a single machine. Engineering Optimization, 52(2), 185–193.

Wang, M. Z., Zhang, L. L., Choi, T. M. (2020). Bi-objective optimal scheduling with raw material’s shelf-life constraints in unrelated parallel machines production. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(11), 4598–4610.

Wang, S., Li, X., Sheng, Q. Z., Beheshti, A. (2022). Performance analysis and optimization on scheduling stochastic cloud service requests: A survey. IEEE Transactions on Network and Service Management,

Wang, Y., Wang, S. (2021). Deploying, scheduling, and sequencing heterogeneous vessels in a liner container shipping route. Transportation Research Part E: Logistics and Transportation Review, 151, 102365.

Wei, W., Li, H., Leus, R. (2017). Test sequencing for sequential system diagnosis with precedence constraints and imperfect tests. Decision Support Systems, 103, 104–116. DOI:

Weiss C. M., Foxx, H., Ben A. S. (2019). A decision support flexible scheduling system for continuous galvanization lines using genetic algorithm. Production Engineering, 13(1), 43–52.

Werner, F., Burtseva, L., Sotskov, Y. N. (2018). Special issue on algorithms for scheduling problems. Algorithms, 11(6), 1–4.

Wisittipanich, W., Hengmeechai, P. (2017). Truck scheduling in multi-door cross docking terminal by modified particle swarm optimization. Computers and Industrial Engineering, 113, 793–802. DOI:

Wu, X, Shen, X., Zhang, L. (2019). Solving the planning and scheduling problem simultaneously in a hospital with a bi-layer discrete particle swarm optimization. Mathematical Biosciences and Engineering, 16(2), 831–861.

Wu, J., Ding, Y., Shi, L. (2021). Mathematical modeling and heuristic approaches for a multi-stage car sequencing problem. Computers and Industrial Engineering, 152, 107008.

Wu, X, Zhou, S. (2022). Sequencing and scheduling appointments on multiple servers with stochastic service durations and customer arrivals. Omega, 106, 102523.

Xian-ru, T. (2012). A Mathematical quadratic integer model based on ant colony optimization for air traffic control. International Journal on Advances in Information Sciences and Service Sciences, 4, 185–191. DOI:

Xu, W., Hu, Y., Luo, W., Wang, L., Wu, R. (2021). A multi-objective scheduling method for distributed and flexible job shop based on hybrid genetic algorithm and tabu search considering operation outsourcing and carbon emission. Computers and Industrial Engineering, 157,

Xu, W., Wu, R., Wang, L., Zhao, X., Li, X. (2022). Solving a multi-objective distributed scheduling problem for building material equipment group enterprises by measuring quality indicator with a product gene evaluation approach. Computers and Industrial Engineering, 168,

Yadav, G., Desai, T. N. (2016). Lean Six Sigma: A categorized review of the literature. International Journal of Lean Six Sigma, 7(1), 2–24. DOI:

Yamada, T. T., Nagano, M. S., Miyata, H. H. (2021). Minimization of total tardiness in no-wait flowshop production systems with preventive maintenance. International Journal of Industrial Engineering Computations, 12(4), 415–426.

Yan, H. Sen, Wan, X. Q., Xiong, F. L. (2014). A hybrid electromagnetism-like algorithm for two-stage assembly flow shop scheduling problem. International Journal of Production Research, 52(19), 5626–5639. DOI:

Yang, Y., Shen, H. (2022). Deep reinforcement learning enhanced greedy optimization for online scheduling of batched tasks in cloud HPC systems. IEEE Transactions on Parallel and Distributed Systems, 33, 3003-3014,

Yeung, W. K., Choi, T. M., Cheng, T. C. E. (2011). Supply chain scheduling and coordination with dual delivery modes and inventory storage cost. International Journal of Production Economics, 132(2), 223–229. DOI:

Yin, Y., Cheng, T. C. E., Xu, D., Wu, C. C. (2012). Common due date assignment and scheduling with a rate-modifying activity to minimize the due date, earliness, tardiness, holding, and batch delivery cost. Computers and Industrial Engineering, 63(1), 223–234. DOI:

Yuan, Y., Ye, S., Lin, L., Gen, M. (2021). Multi-objective multi-mode resource-constrained project scheduling with fuzzy activity durations in prefabricated building construction. Computers and Industrial Engineering, 158, 107316.

Yue, L., Guan, Z., Saif, U., Zhang, F., Wang, H. (2016). Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects. SpringerPlus, 5(1). DOI:

Zhang, F., Mei, Y., Nguyen, S., Zhang, M. (2021). Collaborative multifidelity-based surrogate models for genetic programming in dynamic flexible job shop scheduling. IEEE Transactions on Cybernetics, 1–15.

Zhang, G., Xing, K., Cao, F. (2018). Discrete differential evolution algorithm for distributed blocking flowshop scheduling with makespan criterion. Engineering Applications of Artificial Intelligence, 76(28), 96–107.

Zhang, X., Liu, X., Tang, S., Królczyk, G., Li, Z. (2019). Solving scheduling problem in a distributed manufacturing system using a discrete fruit fly optimization algorithm. Energies, 12(17).

Zhang, Y., D’Ariano, A., He, B., Peng, Q. (2019). Microscopic optimization model and algorithm for integrating train timetabling and track maintenance task scheduling. Transportation Research Part B: Methodological, 127, 237–278.

Zhao, H., Xiang, Y., Shen, Y., Guo, Y., Xue, P., Sun, W., Cai, H., Gu, C., Liu, J. (2022). Resilience assessment of hydrogen-integrated energy system for airport electrification. IEEE Transactions on Industry Applications, 58(2), 2812-2824,

Zhao, X., Huang, C. (2020). Microservice based computational offloading framework and cost efficient task scheduling algorithm in heterogeneous fog cloud network. IEEE Access, 8, 56680–56694.

Zhao, Y., Xu, T., Chakrabarty, K. (2011). Broadcast electrode-addressing and scheduling methods for pin-constrained digital microfluidic biochips. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 30(7), 986–999. DOI:

Zheng, F., Wang, Z., Zhang, E., Liu, M. (2022). K-adaptability in robust container vessel sequencing problem with week-dependent demands of a service route. International Journal of Production Research, 60(9), 2787–2801.

Zhou, S., Yue, Q. (2021a). Appointment scheduling for multi-stage sequential service systems with limited distributional information. Computers and Operations Research, 132, 105287.

Zhou, S., Yue, Q. (2021b). Sequencing and scheduling appointments for multi-stage service systems with stochastic service durations and no-shows. International Journal of Production Research, 60(5), 1500-1519.

Zhou, Y., Yang, J. J., Zheng, L. Y. (2019). Hyper-heuristic coevolution of machine assignment and job sequencing rules for multi-objective dynamic flexible job shop scheduling. IEEE Access, 7, 68–88.

Zhu, X., Ruiz, R., Li, S., Li, X. (2017). An effective heuristic for project scheduling with resource availability cost. European Journal of Operational Research, 257(3), 746–762. DOI:

How to Cite
Bari, P., & Karande, P. (2022). Cost Factor Focused Scheduling and Sequencing: A Neoteric Literature Review. Operational Research in Engineering Sciences: Theory and Applications.