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How to cite this paper
APA: Rossi, F., Boz, E & Nagano, M. (2026). An effective iterated greedy heuristic for the flow shop scheduling with heterogeneous workers. International Journal of Industrial Engineering Computations, 17(2), 709-720.
Chicago/Turabian: Rossi, F., Boz, E & Nagano, M. 2026. "An effective iterated greedy heuristic for the flow shop scheduling with heterogeneous workers." International Journal of Industrial Engineering Computations 17, no. 2 (2026): 709-720.
AMA: Rossi, F., Boz, E & Nagano, M. An effective iterated greedy heuristic for the flow shop scheduling with heterogeneous workers. International Journal of Industrial Engineering Computations. 2026;17(2):709-720.
References
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Becker, T., Neufeld, J., & Buscher, U. (2025). The distributed flow shop scheduling problem with inter-factory transportation. European Journal of Operational Research, 322(1), 39–55.
Benavides, A. J., Ritt, M., & Miralles, C. (2014). Flow shop scheduling with heterogeneous workers. European Journal of Operational Research, 237(3), 713–722.
Benkalai, I., Rebaine, D., & Baptiste, P. (2019). Scheduling flow shops with operators. International Journal of Production Research, 57(2), 338–356.
Blum, C., & Miralles, C. (2011). An introduction to beam search and its application to assembly line worker assignment and
balancing problems. Computers & Operations Research, 38(1), 301–311.
Cheng, T. E., & Kovalyov, M. Y. (2003). Scheduling a single server in a two-machine flow shop. Computing, 70(2), 167–180.
Chu, F., Liu, M., Liu, X., Chu, C., & Jiang, J. (2018). Reentrant flow shop scheduling considering multiresource qualification matching. Scientific Programming, 2018, 2615096.
Corominas, A., Pastor, R., & Plans, J. (2008). Balancing assembly lines with heterogeneous workers. European Journal of Operational Research, 177(1), 264–280.
Fekri, M., Heydari, M., & Mazdeh, M. M. (2024). Bi-objective optimization of flexible flow shop scheduling problem with multi-skilled human resources. Engineering Applications of Artificial Intelligence, 133, 108094.
Fernandez-Viagas, V., & Framinan, J. M. (2014). On insertion tie-breaking rules in heuristics for the permutation flowshop scheduling problem. Computers & Operations Research, 45, 60–67.
Fernandez-Viagas, V., Ruiz, R., & Framiñán, J. M. (2017). A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation. European Journal of Operational Research, 257(3), 707–721.
Fernandez-Viagas, V., Sánchez-Mediano, L., Angulo-Cortés, A., Gómez-Medina, D., & Molina-Pariente, J. M. (2022). The permutation flow shop scheduling problem with human resources: MILP models, decoding procedures, NEH-based heuristics, and an iterated greedy algorithm. Mathematics, 10(19), 3446.
Framiñán, J. M., Leisten, R., & Rajendran, C. (2003). Different initial sequences for the heuristic of Nawaz, Enscore and Ham to minimize makespan, idletime or flowtime in the static permutation flowshop sequencing problem. International Journal of Production Research, 41(1), 121–148.
Garey, M. R., & Johnson, D. S. (1977). Two-processor scheduling with start-times and deadlines. SIAM Journal on Computing, 6(3), 416–426.
Gogos, C. (2023). Solving the distributed permutation flow-shop scheduling problem using constrained programming. Applied Sciences, 13(23), 12562.
Gong, G., Chiong, R., Deng, Q., Han, W., Zhang, L., Lin, W., & Li, K. (2020). Energy-efficient flexible flow shop scheduling with worker flexibility. Expert Systems with Applications, 141, 112902.
Graham, R. L., Lawler, E. L., Lenstra, J. K., & Rinnooy Kan, A. H. G. (1979). Optimization and approximation in deterministic sequencing and scheduling: A survey. Annals of Discrete Mathematics, 5, 287–326.
Irmouli, M., Benazzoug, N., Adimi, A. D., Rezkellah, F. Z., Hamzaoui, I., Hamitouche, T., & Tayeb, F. S. (2023). Genetic algorithm enhanced by deep reinforcement learning in parent selection mechanism and mutation: Minimizing makespan in permutation flow shop scheduling problems. arXiv preprint arXiv:2311.05937.
Komaki, G. M., Sheikh, S., & Malakooti, B. (2019). Flow shop scheduling problems with assembly operations: A review and new trends. International Journal of Production Research, 57(10), 2926–2955.
Li, J., Lin, P., Wu, X., Song, D., Yang, B., & Zhou, L. (2024). Scheduling optimization of ship plane block flow line considering dual resource constraints. Scientific Reports, 14(1), 30765.
Liu, X., Chen, X., Zhao, Y., Liu, X., Wu, C. C., & Lin, W. C. (2025). A multi-objective flexible flow shop scheduling problem with an improved NSGA-II algorithm. Journal of Industrial and Management Optimization, 21(5), 4041–4062.
Liu, Y., Shen, W., Zhang, C., & Sun, X. (2023). Agent-based simulation and optimization of hybrid flow shop considering multi-skilled workers and fatigue factors. Robotics and Computer-Integrated Manufacturing, 80, 102478.
Mansouri, M., Bahmani, Y., & Smadi, H. (2023). Optimization of the Flow-Shop Scheduling Problem under Time Constraints with PSO Algorithm. Engineering Proceedings, 56(1), 220.
Miralles, C., Garcia-Sabater, J. P., Andres, C., & Cardos, M. (2007). Advantages of assembly lines in sheltered work centers for the disabled: A case study. International Journal of Production Research, 45(3), 509–522.
Moreira, M. C., Costa, A. M., & Miralles, C. (2012). Genetic algorithms for the assembly line worker assignment and balancing problem. Expert Systems with Applications, 39(4), 4478–4489.
Nawaz, M., Enscore, E. E., & Ham, I. (1983). A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem. Omega, 11(1), 91–95.
Nicosia, G., Pacifici, A., Pferschy, U., Russo, A. R., & Salvatore, C. (2024). Flow shop scheduling with inter-stage flexibility and blocking constraints. arXiv preprint arXiv:2411.18381.
Pan, Q.-K., & Ruiz, R. (2014). An effective iterated greedy algorithm for the mixed no-idle permutation flowshop scheduling problem. Omega, 44, 41–50.
Park, I., Lee, K., & Pinedo, M. (2025). A flow shop scheduling problem with machine-dependent speeds: An ensemble approach with worst-case analysis. European Journal of Operational Research, 330(2), 373-380.
Rad, S. F., Ruiz, R., & Boroojerdian, N. (2009). New high performing heuristics for minimizing makespan in permutation flowshops. Omega, 37(2), 331-345.
Rossi, F. L., & Nagano, M. S. (2021). Heuristics for the mixed no-idle flowshop with sequence-dependent setup times. Journal of the Operational Research Society, 72(2), 417–443.
Ruiz, R., & Maroto, C. (2005). A comprehensive review and evaluation of permutation flowshop heuristics. European Journal of Operational Research, 165(2), 479–494.
Ruiz, R., & Stützle, T. (2007). A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem. European Journal of Operational Research, 177(3), 2033–2049.
Ruiz, R., & Stützle, T. (2008). An iterated greedy heuristic for the sequence dependent setup times flowshop problem with makespan and weighted tardiness objectives. European Journal of Operational Research, 187(3), 1143–1159.
Samarghandi, H. (2015). Studying the effect of server side-constraints on the makespan of the no-wait flow-shop problem with sequence-dependent set-up times. International Journal of Production Research, 53(9), 2652–2673.
Singla, S., Kaur, H., Gupta, D., Modibbo, U. M., & Kaur, J. (2024). No idle flow shop scheduling models for optimization of machine rental costs with processing and separated setup times. Frontiers in Applied Mathematics and Statistics, 10, 1355237.
Su, Z., Deng, C., Chiong, R., Jiang, S. L., & Zhang, K. (2025). Hybrid flow shop scheduling with continuous processing and resource threshold constraints: A case of steel plant. Expert Systems with Applications, 284, 127247.
Taillard, E. (1993). Benchmarks for basic scheduling problems. European Journal of Operational Research, 64(2), 278–285.
Tasgetiren, M. F., Pan, Q. K., Liang, Y. C., & Suganthan, P. N. (2013). Iterated greedy algorithms for the no-idle flowshop scheduling problem. Computers & Operations Research, 40(7), 1679–1691.
Tosun, Ö., Marichelvam, M. K., & Tosun, N. (2020). A literature review on hybrid flow shop scheduling. International Journal of Advanced Operations Management, 12(2), 156–194.
Becker, T., Neufeld, J., & Buscher, U. (2025). The distributed flow shop scheduling problem with inter-factory transportation. European Journal of Operational Research, 322(1), 39–55.
Benavides, A. J., Ritt, M., & Miralles, C. (2014). Flow shop scheduling with heterogeneous workers. European Journal of Operational Research, 237(3), 713–722.
Benkalai, I., Rebaine, D., & Baptiste, P. (2019). Scheduling flow shops with operators. International Journal of Production Research, 57(2), 338–356.
Blum, C., & Miralles, C. (2011). An introduction to beam search and its application to assembly line worker assignment and
balancing problems. Computers & Operations Research, 38(1), 301–311.
Cheng, T. E., & Kovalyov, M. Y. (2003). Scheduling a single server in a two-machine flow shop. Computing, 70(2), 167–180.
Chu, F., Liu, M., Liu, X., Chu, C., & Jiang, J. (2018). Reentrant flow shop scheduling considering multiresource qualification matching. Scientific Programming, 2018, 2615096.
Corominas, A., Pastor, R., & Plans, J. (2008). Balancing assembly lines with heterogeneous workers. European Journal of Operational Research, 177(1), 264–280.
Fekri, M., Heydari, M., & Mazdeh, M. M. (2024). Bi-objective optimization of flexible flow shop scheduling problem with multi-skilled human resources. Engineering Applications of Artificial Intelligence, 133, 108094.
Fernandez-Viagas, V., & Framinan, J. M. (2014). On insertion tie-breaking rules in heuristics for the permutation flowshop scheduling problem. Computers & Operations Research, 45, 60–67.
Fernandez-Viagas, V., Ruiz, R., & Framiñán, J. M. (2017). A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation. European Journal of Operational Research, 257(3), 707–721.
Fernandez-Viagas, V., Sánchez-Mediano, L., Angulo-Cortés, A., Gómez-Medina, D., & Molina-Pariente, J. M. (2022). The permutation flow shop scheduling problem with human resources: MILP models, decoding procedures, NEH-based heuristics, and an iterated greedy algorithm. Mathematics, 10(19), 3446.
Framiñán, J. M., Leisten, R., & Rajendran, C. (2003). Different initial sequences for the heuristic of Nawaz, Enscore and Ham to minimize makespan, idletime or flowtime in the static permutation flowshop sequencing problem. International Journal of Production Research, 41(1), 121–148.
Garey, M. R., & Johnson, D. S. (1977). Two-processor scheduling with start-times and deadlines. SIAM Journal on Computing, 6(3), 416–426.
Gogos, C. (2023). Solving the distributed permutation flow-shop scheduling problem using constrained programming. Applied Sciences, 13(23), 12562.
Gong, G., Chiong, R., Deng, Q., Han, W., Zhang, L., Lin, W., & Li, K. (2020). Energy-efficient flexible flow shop scheduling with worker flexibility. Expert Systems with Applications, 141, 112902.
Graham, R. L., Lawler, E. L., Lenstra, J. K., & Rinnooy Kan, A. H. G. (1979). Optimization and approximation in deterministic sequencing and scheduling: A survey. Annals of Discrete Mathematics, 5, 287–326.
Irmouli, M., Benazzoug, N., Adimi, A. D., Rezkellah, F. Z., Hamzaoui, I., Hamitouche, T., & Tayeb, F. S. (2023). Genetic algorithm enhanced by deep reinforcement learning in parent selection mechanism and mutation: Minimizing makespan in permutation flow shop scheduling problems. arXiv preprint arXiv:2311.05937.
Komaki, G. M., Sheikh, S., & Malakooti, B. (2019). Flow shop scheduling problems with assembly operations: A review and new trends. International Journal of Production Research, 57(10), 2926–2955.
Li, J., Lin, P., Wu, X., Song, D., Yang, B., & Zhou, L. (2024). Scheduling optimization of ship plane block flow line considering dual resource constraints. Scientific Reports, 14(1), 30765.
Liu, X., Chen, X., Zhao, Y., Liu, X., Wu, C. C., & Lin, W. C. (2025). A multi-objective flexible flow shop scheduling problem with an improved NSGA-II algorithm. Journal of Industrial and Management Optimization, 21(5), 4041–4062.
Liu, Y., Shen, W., Zhang, C., & Sun, X. (2023). Agent-based simulation and optimization of hybrid flow shop considering multi-skilled workers and fatigue factors. Robotics and Computer-Integrated Manufacturing, 80, 102478.
Mansouri, M., Bahmani, Y., & Smadi, H. (2023). Optimization of the Flow-Shop Scheduling Problem under Time Constraints with PSO Algorithm. Engineering Proceedings, 56(1), 220.
Miralles, C., Garcia-Sabater, J. P., Andres, C., & Cardos, M. (2007). Advantages of assembly lines in sheltered work centers for the disabled: A case study. International Journal of Production Research, 45(3), 509–522.
Moreira, M. C., Costa, A. M., & Miralles, C. (2012). Genetic algorithms for the assembly line worker assignment and balancing problem. Expert Systems with Applications, 39(4), 4478–4489.
Nawaz, M., Enscore, E. E., & Ham, I. (1983). A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem. Omega, 11(1), 91–95.
Nicosia, G., Pacifici, A., Pferschy, U., Russo, A. R., & Salvatore, C. (2024). Flow shop scheduling with inter-stage flexibility and blocking constraints. arXiv preprint arXiv:2411.18381.
Pan, Q.-K., & Ruiz, R. (2014). An effective iterated greedy algorithm for the mixed no-idle permutation flowshop scheduling problem. Omega, 44, 41–50.
Park, I., Lee, K., & Pinedo, M. (2025). A flow shop scheduling problem with machine-dependent speeds: An ensemble approach with worst-case analysis. European Journal of Operational Research, 330(2), 373-380.
Rad, S. F., Ruiz, R., & Boroojerdian, N. (2009). New high performing heuristics for minimizing makespan in permutation flowshops. Omega, 37(2), 331-345.
Rossi, F. L., & Nagano, M. S. (2021). Heuristics for the mixed no-idle flowshop with sequence-dependent setup times. Journal of the Operational Research Society, 72(2), 417–443.
Ruiz, R., & Maroto, C. (2005). A comprehensive review and evaluation of permutation flowshop heuristics. European Journal of Operational Research, 165(2), 479–494.
Ruiz, R., & Stützle, T. (2007). A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem. European Journal of Operational Research, 177(3), 2033–2049.
Ruiz, R., & Stützle, T. (2008). An iterated greedy heuristic for the sequence dependent setup times flowshop problem with makespan and weighted tardiness objectives. European Journal of Operational Research, 187(3), 1143–1159.
Samarghandi, H. (2015). Studying the effect of server side-constraints on the makespan of the no-wait flow-shop problem with sequence-dependent set-up times. International Journal of Production Research, 53(9), 2652–2673.
Singla, S., Kaur, H., Gupta, D., Modibbo, U. M., & Kaur, J. (2024). No idle flow shop scheduling models for optimization of machine rental costs with processing and separated setup times. Frontiers in Applied Mathematics and Statistics, 10, 1355237.
Su, Z., Deng, C., Chiong, R., Jiang, S. L., & Zhang, K. (2025). Hybrid flow shop scheduling with continuous processing and resource threshold constraints: A case of steel plant. Expert Systems with Applications, 284, 127247.
Taillard, E. (1993). Benchmarks for basic scheduling problems. European Journal of Operational Research, 64(2), 278–285.
Tasgetiren, M. F., Pan, Q. K., Liang, Y. C., & Suganthan, P. N. (2013). Iterated greedy algorithms for the no-idle flowshop scheduling problem. Computers & Operations Research, 40(7), 1679–1691.
Tosun, Ö., Marichelvam, M. K., & Tosun, N. (2020). A literature review on hybrid flow shop scheduling. International Journal of Advanced Operations Management, 12(2), 156–194.