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A particle swarm optimization algorithm for makespan and total flowtime minimization in the permutation flowshop sequencing problem

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  1. Boonmee, Atiwat & Sethanan, Kanchana, 2016. "A GLNPSO for multi-level capacitated lot-sizing and scheduling problem in the poultry industry," European Journal of Operational Research, Elsevier, vol. 250(2), pages 652-665.
  2. Zühal Kartal & Mohan Krishnamoorthy & Andreas T. Ernst, 2019. "Heuristic algorithms for the single allocation p-hub center problem with routing considerations," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(1), pages 99-145, March.
  3. Kalczynski, Pawel J. & Kamburowski, Jerzy, 2009. "An empirical analysis of the optimality rate of flow shop heuristics," European Journal of Operational Research, Elsevier, vol. 198(1), pages 93-101, October.
  4. Sündüz Dağ, 2013. "An Application On Flowshop Scheduling," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 1(1), pages 47-56, December.
  5. Chang, Pei-Chann & Huang, Wei-Hsiu & Wu, Jheng-Long & Cheng, T.C.E., 2013. "A block mining and re-combination enhanced genetic algorithm for the permutation flowshop scheduling problem," International Journal of Production Economics, Elsevier, vol. 141(1), pages 45-55.
  6. Chen, Yin-Yann & Cheng, Chen-Yang & Wang, Li-Chih & Chen, Tzu-Li, 2013. "A hybrid approach based on the variable neighborhood search and particle swarm optimization for parallel machine scheduling problems—A case study for solar cell industry," International Journal of Production Economics, Elsevier, vol. 141(1), pages 66-78.
  7. Zhang, Yi & Li, Xiaoping & Wang, Qian, 2009. "Hybrid genetic algorithm for permutation flowshop scheduling problems with total flowtime minimization," European Journal of Operational Research, Elsevier, vol. 196(3), pages 869-876, August.
  8. Albert Corominas & Alberto García-Villoria & Rafael Pastor, 2013. "Metaheuristic algorithms hybridised with variable neighbourhood search for solving the response time variability problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(2), pages 296-312, July.
  9. Shesh Narayan Sahu & Yuvraj Gajpal & Swapan Debbarma, 2018. "Two-agent-based single-machine scheduling with switchover time to minimize total weighted completion time and makespan objectives," Annals of Operations Research, Springer, vol. 269(1), pages 623-640, October.
  10. Öztürkoğlu, Ö. & Gue, K.R. & Meller, R.D., 2014. "A constructive aisle design model for unit-load warehouses with multiple pickup and deposit points," European Journal of Operational Research, Elsevier, vol. 236(1), pages 382-394.
  11. Neungmatcha, Woraya, 2016. "Multi-objective particle swarm optimization for mechanical harvester route planning of sugarcane field operationsAuthor-Name: Sethanan, Kanchana," European Journal of Operational Research, Elsevier, vol. 252(3), pages 969-984.
  12. Jacomine Grobler & Andries Engelbrecht & Schalk Kok & Sarma Yadavalli, 2010. "Metaheuristics for the multi-objective FJSP with sequence-dependent set-up times, auxiliary resources and machine down time," Annals of Operations Research, Springer, vol. 180(1), pages 165-196, November.
  13. Divya Chaudhary & Bijendra Kumar, 2018. "A New Balanced Particle Swarm Optimisation for Load Scheduling in Cloud Computing," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-23, March.
  14. Pan, Quan-Ke & Ruiz, Rubén, 2012. "Local search methods for the flowshop scheduling problem with flowtime minimization," European Journal of Operational Research, Elsevier, vol. 222(1), pages 31-43.
  15. Quang Chieu Ta & Jean-Charles Billaut & Jean-Louis Bouquard, 2018. "Matheuristic algorithms for minimizing total tardiness in the m-machine flow-shop scheduling problem," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 617-628, March.
  16. Hadi Mokhtari & Amir Noroozi, 2018. "An efficient chaotic based PSO for earliness/tardiness optimization in a batch processing flow shop scheduling problem," Journal of Intelligent Manufacturing, Springer, vol. 29(5), pages 1063-1081, June.
  17. Tseng, Lin-Yu & Lin, Ya-Tai, 2009. "A hybrid genetic local search algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 198(1), pages 84-92, October.
  18. Qi, Jie & Rong, Zhihai, 2013. "The emergence of scaling laws search dynamics in a particle swarm optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1522-1531.
  19. Al-Anzi, Fawaz S. & Allahverdi, Ali, 2007. "A self-adaptive differential evolution heuristic for two-stage assembly scheduling problem to minimize maximum lateness with setup times," European Journal of Operational Research, Elsevier, vol. 182(1), pages 80-94, October.
  20. Pagnozzi, Federico & Stützle, Thomas, 2019. "Automatic design of hybrid stochastic local search algorithms for permutation flowshop problems," European Journal of Operational Research, Elsevier, vol. 276(2), pages 409-421.
  21. Cho, Huidae & Kim, Dongkyun & Olivera, Francisco & Guikema, Seth D., 2011. "Enhanced speciation in particle swarm optimization for multi-modal problems," European Journal of Operational Research, Elsevier, vol. 213(1), pages 15-23, August.
  22. Etgar, Ran & Gelbard, Roy & Cohen, Yuval, 2017. "Optimizing version release dates of research and development long-term processes," European Journal of Operational Research, Elsevier, vol. 259(2), pages 642-653.
  23. G I Zobolas & C D Tarantilis & G Ioannou, 2009. "A hybrid evolutionary algorithm for the job shop scheduling problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(2), pages 221-235, February.
  24. Bo Liu & Ling Wang & Ying Liu & Shouyang Wang, 2011. "A unified framework for population-based metaheuristics," Annals of Operations Research, Springer, vol. 186(1), pages 231-262, June.
  25. Imen Hamdi & Imen Boujneh, 2022. "Particle swarm optimization based-algorithms to solve the two-machine cross-docking flow shop problem: just in time scheduling," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 947-969, September.
  26. Zhou, Hong & Cheung, Waiman & Leung, Lawrence C., 2009. "Minimizing weighted tardiness of job-shop scheduling using a hybrid genetic algorithm," European Journal of Operational Research, Elsevier, vol. 194(3), pages 637-649, May.
  27. Branislav Micieta & Jolanta Staszewska & Matej Kovalsky & Martin Krajcovic & Vladimira Binasova & Ladislav Papanek & Ivan Antoniuk, 2021. "Innovative System for Scheduling Production Using a Combination of Parametric Simulation Models," Sustainability, MDPI, vol. 13(17), pages 1-20, August.
  28. Jakubik, Johannes & Binding, Adrian & Feuerriegel, Stefan, 2021. "Directed particle swarm optimization with Gaussian-process-based function forecasting," European Journal of Operational Research, Elsevier, vol. 295(1), pages 157-169.
  29. Libin Han & Keyi Xing & Xiao Chen & Fuli Xiong, 2018. "A Petri net-based particle swarm optimization approach for scheduling deadlock-prone flexible manufacturing systems," Journal of Intelligent Manufacturing, Springer, vol. 29(5), pages 1083-1096, June.
  30. Anghinolfi, Davide & Paolucci, Massimo, 2009. "A new discrete particle swarm optimization approach for the single-machine total weighted tardiness scheduling problem with sequence-dependent setup times," European Journal of Operational Research, Elsevier, vol. 193(1), pages 73-85, February.
  31. Fontes, Dalila B.M.M. & Homayouni, S. Mahdi & Gonçalves, José F., 2023. "A hybrid particle swarm optimization and simulated annealing algorithm for the job shop scheduling problem with transport resources," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1140-1157.
  32. Broderick Crawford & Ricardo Soto & Gino Astorga & José García & Carlos Castro & Fernando Paredes, 2017. "Putting Continuous Metaheuristics to Work in Binary Search Spaces," Complexity, Hindawi, vol. 2017, pages 1-19, May.
  33. Pan, Quan-Ke & Gao, Liang & Li, Xin-Yu & Gao, Kai-Zhou, 2017. "Effective metaheuristics for scheduling a hybrid flowshop with sequence-dependent setup times," Applied Mathematics and Computation, Elsevier, vol. 303(C), pages 89-112.
  34. Benavides, Alexander J. & Ritt, Marcus & Miralles, Cristóbal, 2014. "Flow shop scheduling with heterogeneous workers," European Journal of Operational Research, Elsevier, vol. 237(2), pages 713-720.
  35. Fernandez-Viagas, Victor & Ruiz, Rubén & Framinan, Jose 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, Elsevier, vol. 257(3), pages 707-721.
  36. Pierre Hansen & Nenad Mladenović & José Moreno Pérez, 2010. "Variable neighbourhood search: methods and applications," Annals of Operations Research, Springer, vol. 175(1), pages 367-407, March.
  37. Tseng, Lin-Yu & Lin, Ya-Tai, 2010. "A genetic local search algorithm for minimizing total flowtime in the permutation flowshop scheduling problem," International Journal of Production Economics, Elsevier, vol. 127(1), pages 121-128, September.
  38. Tseng, Chao-Tang & Liao, Ching-Jong, 2008. "A discrete particle swarm optimization for lot-streaming flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 191(2), pages 360-373, December.
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