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The effect of various operators on the genetic search for large scheduling problems

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  • Nearchou, A.C.Andreas C.

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  • Nearchou, A.C.Andreas C., 2004. "The effect of various operators on the genetic search for large scheduling problems," International Journal of Production Economics, Elsevier, vol. 88(2), pages 191-203, March.
    • Handle: RePEc:eee:proeco:v:88:y:2004:i:2:p:191-203
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    1. Ishibuchi, Hisao & Misaki, Shinta & Tanaka, Hideo, 1995. "Modified simulated annealing algorithms for the flow shop sequencing problem," European Journal of Operational Research, Elsevier, vol. 81(2), pages 388-398, March.
    2. Osman, IH & Potts, CN, 1989. "Simulated annealing for permutation flow-shop scheduling," Omega, Elsevier, vol. 17(6), pages 551-557.
    3. Nawaz, Muhammad & Enscore Jr, E Emory & Ham, Inyong, 1983. "A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem," Omega, Elsevier, vol. 11(1), pages 91-95.
    4. David G. Dannenbring, 1977. "An Evaluation of Flow Shop Sequencing Heuristics," Management Science, INFORMS, vol. 23(11), pages 1174-1182, July.
    5. Herbert G. Campbell & Richard A. Dudek & Milton L. Smith, 1970. "A Heuristic Algorithm for the n Job, m Machine Sequencing Problem," Management Science, INFORMS, vol. 16(10), pages 630-637, June.
    6. Taillard, E., 1990. "Some efficient heuristic methods for the flow shop sequencing problem," European Journal of Operational Research, Elsevier, vol. 47(1), pages 65-74, July.
    7. Taillard, E., 1993. "Benchmarks for basic scheduling problems," European Journal of Operational Research, Elsevier, vol. 64(2), pages 278-285, January.
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    Cited by:

    1. Keskinturk, Timur & Er, Sebnem, 2007. "A genetic algorithm approach to determine stratum boundaries and sample sizes of each stratum in stratified sampling," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 53-67, September.
    2. K A H Kobbacy & S Vadera & M H Rasmy, 2007. "AI and OR in management of operations: history and trends," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(1), pages 10-28, January.
    3. 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.
    4. Lian, Zhigang & Gu, Xingsheng & Jiao, Bin, 2008. "A novel particle swarm optimization algorithm for permutation flow-shop scheduling to minimize makespan," Chaos, Solitons & Fractals, Elsevier, vol. 35(5), pages 851-861.
    5. Naso, David & Surico, Michele & Turchiano, Biagio & Kaymak, Uzay, 2007. "Genetic algorithms for supply-chain scheduling: A case study in the distribution of ready-mixed concrete," European Journal of Operational Research, Elsevier, vol. 177(3), pages 2069-2099, March.
    6. 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.
    7. Nikolaos Charalambopoulos & Andreas C. Nearchou, 2021. "Ship Routing Using Genetic Algorithms," SN Operations Research Forum, Springer, vol. 2(3), pages 1-26, September.
    8. Damodaran, Purushothaman & Kumar Manjeshwar, Praveen & Srihari, Krishnaswami, 2006. "Minimizing makespan on a batch-processing machine with non-identical job sizes using genetic algorithms," International Journal of Production Economics, Elsevier, vol. 103(2), pages 882-891, October.
    9. 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.
    10. Maryam Mousavi & Hwa Jen Yap & Siti Nurmaya Musa & Farzad Tahriri & Siti Zawiah Md Dawal, 2017. "Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-24, March.

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