How to cite this paper
Li, C., Li, Y., Meng, L & Zhang, B. (2025). A hybrid artificial bee colony algorithm with an iterated local search mechanism for distributed no-wait flowshop problems with preventive maintenance.International Journal of Industrial Engineering Computations , 16(2), 307-322.
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References
Aldowaisan, T. & Allahverdi, A. (2004). New heuristics for m-machine no-wait flowshop to minimize total completion time. Omega-International Journal of Management Science, 32(5), 345-352.
Allahverdi, A. (2015). The third comprehensive survey on scheduling problems with setup times/costs. European Journal of Operational Research, 246(2), 345-378.
Allahverdi, A., Ng, C.T., Cheng, T.C.E. & Kovalyov, M.Y. (2008). A survey of scheduling problems with setup times or costs. European Journal of Operational Research, 187(3), 985-1032.
Allali, K., Aqil, S. & Belabid, J. (2022). Distributed no-wait flow shop problem with sequence dependent setup time: Optimization of makespan and maximum tardiness. Simulation Modelling Practice and Theory, 116, 102455.
Cheng, C., Ying, K., Chen, H. & Lu, H. (2019). Minimising makespan in distributed mixed no-idle flowshops. International Journal of Production Research, 57(1), 48-60.
Fernandez-Viagas, V. & Framinan, J.M. (2014). A bounded-search iterated greedy algorithm for the distributed permutation flowshop scheduling problem. International Journal of Production Research, 53(4), 1111-1123.
Fernandez-Viagas, V., Perez-Gonzalez, P. & Framinan, J.M. (2018). The distributed permutation flow shop to minimise the total flowtime. Computers & Industrial Engineering, 118, 464-477.
Fitouhi, M. & Nourelfath, M. (2012). Integrating noncyclical preventive maintenance scheduling and production planning for a single machine. International Journal of Production Economics, 136(2), 344-351.
Gao, J., Chen, R. & Deng, W. (2013). An efficient tabu search algorithm for the distributed permutation flowshop scheduling problem. International Journal of Production Research, 51(3), 641-651.
Gao, K., Pan, Q. & Li, J. (2011). Discrete harmony search algorithm for the no-wait flow shop scheduling problem with total flow time criterion. The International Journal of Advanced Manufacturing Technology, 56(5-8), 683-692.
Han, X., Han, Y., Zhang, B., Qin, H., Li, J., Liu, Y. & Gong, D. (2022). An effective iterative greedy algorithm for distributed blocking flowshop scheduling problem with balanced energy costs criterion. Applied Soft Computing, 129,109502.
Hans, R.C. (1984). The Three-Machine No-Wait Flow Shop Is NP-Complete. Journal of the Acm, 31, 336-345.
Jia, H.Z., Fuh, J.Y.H., Nee, A.Y.C. & Zhang, Y.F. (2007). Integration of genetic algorithm and Gantt chart for job shop scheduling in distributed manufacturing systems. Computers & Industrial Engineering, 53(2), 313-320.
Jing, X., Pan, Q. & Gao, L. (2021). Local search-based metaheuristics for the robust distributed permutation flowshop problem. Applied Soft Computing, 105, 107247.
Lei, D. & Liu, M. (2020). An artificial bee colony with division for distributed unrelated parallel machine scheduling with preventive maintenance. Computers & Industrial Engineering, 141, 106320.
Li, H., Li, X. & Gao, L. (2021). A discrete artificial bee colony algorithm for the distributed heterogeneous no-wait flowshop scheduling problem. Applied Soft Computing, 100, 106946.
Li, Y., Pan, Q., Li, J., Gao, L. & Tasgetiren, M.F. (2021). An Adaptive Iterated Greedy algorithm for distributed mixed no-idle permutation flowshop scheduling problems. Swarm and Evolutionary Computation, 63, 100874.
Li, Y., Pan, Q., Ruiz, R. & Sang, H. (2022). A referenced iterated greedy algorithm for the distributed assembly mixed no-idle permutation flowshop scheduling problem with the total tardiness criterion. Knowledge-Based Systems, 239(3), 108036.
Lu, C., Liu, Q., Zhang, B. & Yin, L. (2022). A Pareto-based hybrid iterated greedy algorithm for energy-efficient scheduling of distributed hybrid flowshop. Expert Systems with Applications, 204, 117555.
Mao, J., Pan, Q., Miao, Z. & Gao, L. (2021). An effective multi-start iterated greedy algorithm to minimize makespan for the distributed permutation flowshop scheduling problem with preventive maintenance. Expert Systems with Applications, 169(5).
Mao, J., Pan, Q., Miao, Z., Gao, L. & Chen, S. (2022). A hash map-based memetic algorithm for the distributed permutation flowshop scheduling problem with preventive maintenance to minimize total flowtime. Knowledge-Based Systems, 242(4), 108413.
Meng, K., Tang, Q., Cheng, L. & Zhang, Z. (2022). Mixed-model assembly line balancing problem considering preventive maintenance scenarios: MILP model and cooperative co-evolutionary algorithm. Applied Soft Computing, 127,109341.
Meng, L., Gao, K., Ren, Y., Zhang, B., Sang, H. & Chaoyong, Z. (2022). Novel MILP and CP models for distributed hybrid flowshop scheduling problem with sequence-dependent setup times. Swarm and Evolutionary Computation, 71, 101058.
Miyata, H.H. & Nagano, M.S. (2021). Optimizing distributed no-wait flow shop scheduling problem with setup times and maintenance operations via iterated greedy algorithm. Journal of Manufacturing Systems, 61, 592-612.
Miyata, H.H., Nagano, M.S. & Gupta, J.N.D. (2019). Integrating preventive maintenance activities to the no-wait flow shop scheduling problem with dependent-sequence setup times and makespan minimization. Computers & Industrial Engineering, 135,79-104.
Naderi, B. & Ruiz, R. (2010). The distributed permutation flowshop scheduling problem. Computers & Operations Research, 37(4), 754-768.
Naderi, B., Zandieh, M. & Aminnayeri, M. (2011). Incorporating periodic preventive maintenance into flexible flowshop scheduling problems. Applied Soft Computing, 11(2), 2094-2101.
Pan, E., Liao, W. & Xi, L. (2010). Single-machine-based production scheduling model integrated preventive maintenance planning. The International Journal of Advanced Manufacturing Technology, 50(1), 365-375.
Pan, Q., Gao, L., Li, X. & Jose, F.M. (2019). Effective constructive heuristics and meta-heuristics for the distributed assembly permutation flowshop scheduling problem. Applied Soft Computing, 81,105492.
Pan, Q., Gao, L., Wang, L., Liang, J. & Li, X. (2019). Effective heuristics and metaheuristics to minimize total flowtime for the distributed permutation flowshop problem. Expert Systems with Applications, 124, 309-324.
Pan, Q., Wang, L. & Zhao, B. (2008). An improved iterated greedy algorithm for the no-wait flow shop scheduling problem with makespan criterion. The International Journal of Advanced Manufacturing Technology, 38(7), 778-786.
Pan, Q., Zhao, B. & Qu, Y. (2008). Heuristics for the No-Wait Flow Shop Problem with Makespan Criterion. Chinese Journal of Computers, 31,1147-1154.
Pei, Z., Zhang, X., Zheng, L. & Wan, M. (2019). A column generation-based approach for proportionate flexible two-stage no-wait job shop scheduling. International Journal of Production Research, 58, 487-508.
Rossi, F.L. & Nagano, M.S. (2021). Heuristics and iterated greedy algorithms for the distributed mixed no-idle flowshop with sequence-dependent setup times. Computers & Industrial Engineering, 157,107337.
Ruiz, R., Carlos García-Díaz, J. & Maroto, C. (2007). Considering scheduling and preventive maintenance in the flowshop sequencing problem. Computers & Operations Research, 34(11), 3314-3330.
Shao, W., Shao, Z. & Pi, D. (2021). Effective constructive heuristics for distributed no-wait flexible flow shop scheduling problem. Computers & Operations Research, 136, 105482.
Tseng, L. & Lin, Y. (2010). A hybrid genetic algorithm for no-wait flowshop scheduling problem. International Journal of Production Economics, 128(1),144-152.
Wang, H. (2002). A survey of maintenance policies of deteriorating systems. European Journal of Operational Research, 139(3), 469-489.
Wang, S., Wang, L., Liu, M. & Xu, Y. (2013). An effective estimation of distribution algorithm for solving the distributed permutation flow-shop scheduling problem. International Journal of Production Economics, 145(1), 387-396.
Yang, S., Wang, J. & Xu, Z. (2022). Real-time scheduling for distributed permutation flowshops with dynamic job arrivals using deep reinforcement learning. Advanced Engineering Informatics, 54, 101776.
Ye, H., Li, W. & Abedini, A. (2017). An improved heuristic for no-wait flow shop to minimize makespan. Journal of Manufacturing Systems, 44 ,273-279.
Ying, K. & Lin, S. (2020). Solving no-wait job-shop scheduling problems using a multi-start simulated annealing with bi-directional shift timetabling algorithm. Computers & Industrial Engineering, 146, 106615.
Ying, K., Lin, S., Cheng, C. & He, C. (2017). Iterated reference greedy algorithm for solving distributed no-idle permutation flowshop scheduling problems. Computers & Industrial Engineering, 110, 413-423.
Yu, Y., Zhang, F., Yang, G., Wang, Y., Huang, J. & Han, Y. (2022). A discrete artificial bee colony method based on variable neighborhood structures for the distributed permutation flowshop problem with sequence-dependent setup times. Swarm and Evolutionary Computation, 75, 101179.
Zhu, N.N., Zhao, F.Q., Wang, L., Ding, R.Q., Xu, T.P. & Jonrinaldi. (2022). A discrete learning fruit fly algorithm based on knowledge for the distributed no-wait flow shop scheduling with due windows. Expert Systems with Applications, 198.
Aldowaisan, T. & Allahverdi, A. (2004). New heuristics for m-machine no-wait flowshop to minimize total completion time. Omega-International Journal of Management Science, 32(5), 345-352.
Allahverdi, A. (2015). The third comprehensive survey on scheduling problems with setup times/costs. European Journal of Operational Research, 246(2), 345-378.
Allahverdi, A., Ng, C.T., Cheng, T.C.E. & Kovalyov, M.Y. (2008). A survey of scheduling problems with setup times or costs. European Journal of Operational Research, 187(3), 985-1032.
Allali, K., Aqil, S. & Belabid, J. (2022). Distributed no-wait flow shop problem with sequence dependent setup time: Optimization of makespan and maximum tardiness. Simulation Modelling Practice and Theory, 116, 102455.
Cheng, C., Ying, K., Chen, H. & Lu, H. (2019). Minimising makespan in distributed mixed no-idle flowshops. International Journal of Production Research, 57(1), 48-60.
Fernandez-Viagas, V. & Framinan, J.M. (2014). A bounded-search iterated greedy algorithm for the distributed permutation flowshop scheduling problem. International Journal of Production Research, 53(4), 1111-1123.
Fernandez-Viagas, V., Perez-Gonzalez, P. & Framinan, J.M. (2018). The distributed permutation flow shop to minimise the total flowtime. Computers & Industrial Engineering, 118, 464-477.
Fitouhi, M. & Nourelfath, M. (2012). Integrating noncyclical preventive maintenance scheduling and production planning for a single machine. International Journal of Production Economics, 136(2), 344-351.
Gao, J., Chen, R. & Deng, W. (2013). An efficient tabu search algorithm for the distributed permutation flowshop scheduling problem. International Journal of Production Research, 51(3), 641-651.
Gao, K., Pan, Q. & Li, J. (2011). Discrete harmony search algorithm for the no-wait flow shop scheduling problem with total flow time criterion. The International Journal of Advanced Manufacturing Technology, 56(5-8), 683-692.
Han, X., Han, Y., Zhang, B., Qin, H., Li, J., Liu, Y. & Gong, D. (2022). An effective iterative greedy algorithm for distributed blocking flowshop scheduling problem with balanced energy costs criterion. Applied Soft Computing, 129,109502.
Hans, R.C. (1984). The Three-Machine No-Wait Flow Shop Is NP-Complete. Journal of the Acm, 31, 336-345.
Jia, H.Z., Fuh, J.Y.H., Nee, A.Y.C. & Zhang, Y.F. (2007). Integration of genetic algorithm and Gantt chart for job shop scheduling in distributed manufacturing systems. Computers & Industrial Engineering, 53(2), 313-320.
Jing, X., Pan, Q. & Gao, L. (2021). Local search-based metaheuristics for the robust distributed permutation flowshop problem. Applied Soft Computing, 105, 107247.
Lei, D. & Liu, M. (2020). An artificial bee colony with division for distributed unrelated parallel machine scheduling with preventive maintenance. Computers & Industrial Engineering, 141, 106320.
Li, H., Li, X. & Gao, L. (2021). A discrete artificial bee colony algorithm for the distributed heterogeneous no-wait flowshop scheduling problem. Applied Soft Computing, 100, 106946.
Li, Y., Pan, Q., Li, J., Gao, L. & Tasgetiren, M.F. (2021). An Adaptive Iterated Greedy algorithm for distributed mixed no-idle permutation flowshop scheduling problems. Swarm and Evolutionary Computation, 63, 100874.
Li, Y., Pan, Q., Ruiz, R. & Sang, H. (2022). A referenced iterated greedy algorithm for the distributed assembly mixed no-idle permutation flowshop scheduling problem with the total tardiness criterion. Knowledge-Based Systems, 239(3), 108036.
Lu, C., Liu, Q., Zhang, B. & Yin, L. (2022). A Pareto-based hybrid iterated greedy algorithm for energy-efficient scheduling of distributed hybrid flowshop. Expert Systems with Applications, 204, 117555.
Mao, J., Pan, Q., Miao, Z. & Gao, L. (2021). An effective multi-start iterated greedy algorithm to minimize makespan for the distributed permutation flowshop scheduling problem with preventive maintenance. Expert Systems with Applications, 169(5).
Mao, J., Pan, Q., Miao, Z., Gao, L. & Chen, S. (2022). A hash map-based memetic algorithm for the distributed permutation flowshop scheduling problem with preventive maintenance to minimize total flowtime. Knowledge-Based Systems, 242(4), 108413.
Meng, K., Tang, Q., Cheng, L. & Zhang, Z. (2022). Mixed-model assembly line balancing problem considering preventive maintenance scenarios: MILP model and cooperative co-evolutionary algorithm. Applied Soft Computing, 127,109341.
Meng, L., Gao, K., Ren, Y., Zhang, B., Sang, H. & Chaoyong, Z. (2022). Novel MILP and CP models for distributed hybrid flowshop scheduling problem with sequence-dependent setup times. Swarm and Evolutionary Computation, 71, 101058.
Miyata, H.H. & Nagano, M.S. (2021). Optimizing distributed no-wait flow shop scheduling problem with setup times and maintenance operations via iterated greedy algorithm. Journal of Manufacturing Systems, 61, 592-612.
Miyata, H.H., Nagano, M.S. & Gupta, J.N.D. (2019). Integrating preventive maintenance activities to the no-wait flow shop scheduling problem with dependent-sequence setup times and makespan minimization. Computers & Industrial Engineering, 135,79-104.
Naderi, B. & Ruiz, R. (2010). The distributed permutation flowshop scheduling problem. Computers & Operations Research, 37(4), 754-768.
Naderi, B., Zandieh, M. & Aminnayeri, M. (2011). Incorporating periodic preventive maintenance into flexible flowshop scheduling problems. Applied Soft Computing, 11(2), 2094-2101.
Pan, E., Liao, W. & Xi, L. (2010). Single-machine-based production scheduling model integrated preventive maintenance planning. The International Journal of Advanced Manufacturing Technology, 50(1), 365-375.
Pan, Q., Gao, L., Li, X. & Jose, F.M. (2019). Effective constructive heuristics and meta-heuristics for the distributed assembly permutation flowshop scheduling problem. Applied Soft Computing, 81,105492.
Pan, Q., Gao, L., Wang, L., Liang, J. & Li, X. (2019). Effective heuristics and metaheuristics to minimize total flowtime for the distributed permutation flowshop problem. Expert Systems with Applications, 124, 309-324.
Pan, Q., Wang, L. & Zhao, B. (2008). An improved iterated greedy algorithm for the no-wait flow shop scheduling problem with makespan criterion. The International Journal of Advanced Manufacturing Technology, 38(7), 778-786.
Pan, Q., Zhao, B. & Qu, Y. (2008). Heuristics for the No-Wait Flow Shop Problem with Makespan Criterion. Chinese Journal of Computers, 31,1147-1154.
Pei, Z., Zhang, X., Zheng, L. & Wan, M. (2019). A column generation-based approach for proportionate flexible two-stage no-wait job shop scheduling. International Journal of Production Research, 58, 487-508.
Rossi, F.L. & Nagano, M.S. (2021). Heuristics and iterated greedy algorithms for the distributed mixed no-idle flowshop with sequence-dependent setup times. Computers & Industrial Engineering, 157,107337.
Ruiz, R., Carlos García-Díaz, J. & Maroto, C. (2007). Considering scheduling and preventive maintenance in the flowshop sequencing problem. Computers & Operations Research, 34(11), 3314-3330.
Shao, W., Shao, Z. & Pi, D. (2021). Effective constructive heuristics for distributed no-wait flexible flow shop scheduling problem. Computers & Operations Research, 136, 105482.
Tseng, L. & Lin, Y. (2010). A hybrid genetic algorithm for no-wait flowshop scheduling problem. International Journal of Production Economics, 128(1),144-152.
Wang, H. (2002). A survey of maintenance policies of deteriorating systems. European Journal of Operational Research, 139(3), 469-489.
Wang, S., Wang, L., Liu, M. & Xu, Y. (2013). An effective estimation of distribution algorithm for solving the distributed permutation flow-shop scheduling problem. International Journal of Production Economics, 145(1), 387-396.
Yang, S., Wang, J. & Xu, Z. (2022). Real-time scheduling for distributed permutation flowshops with dynamic job arrivals using deep reinforcement learning. Advanced Engineering Informatics, 54, 101776.
Ye, H., Li, W. & Abedini, A. (2017). An improved heuristic for no-wait flow shop to minimize makespan. Journal of Manufacturing Systems, 44 ,273-279.
Ying, K. & Lin, S. (2020). Solving no-wait job-shop scheduling problems using a multi-start simulated annealing with bi-directional shift timetabling algorithm. Computers & Industrial Engineering, 146, 106615.
Ying, K., Lin, S., Cheng, C. & He, C. (2017). Iterated reference greedy algorithm for solving distributed no-idle permutation flowshop scheduling problems. Computers & Industrial Engineering, 110, 413-423.
Yu, Y., Zhang, F., Yang, G., Wang, Y., Huang, J. & Han, Y. (2022). A discrete artificial bee colony method based on variable neighborhood structures for the distributed permutation flowshop problem with sequence-dependent setup times. Swarm and Evolutionary Computation, 75, 101179.
Zhu, N.N., Zhao, F.Q., Wang, L., Ding, R.Q., Xu, T.P. & Jonrinaldi. (2022). A discrete learning fruit fly algorithm based on knowledge for the distributed no-wait flow shop scheduling with due windows. Expert Systems with Applications, 198.