IDEAS home Printed from https://ideas.repec.org/r/eee/jomega/v34y2006i5p461-476.html
   My bibliography  Save this item

Two new robust genetic algorithms for the flowshop scheduling problem

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Wahiba Jomaa & Mansour Eddaly & Bassem Jarboui, 2021. "Variable neighborhood search algorithms for the permutation flowshop scheduling problem with the preventive maintenance," Operational Research, Springer, vol. 21(4), pages 2525-2542, December.
  2. Hu, Luoke & Liu, Ying & Peng, Chen & Tang, Wangchujun & Tang, Renzhong & Tiwari, Ashutosh, 2018. "Minimising the energy consumption of tool change and tool path of machining by sequencing the features," Energy, Elsevier, vol. 147(C), pages 390-402.
  3. Li, Gang & Jiang, Hongxun & He, Tian, 2015. "A genetic algorithm-based decomposition approach to solve an integrated equipment-workforce-service planning problem," Omega, Elsevier, vol. 50(C), pages 1-17.
  4. Vallada, Eva & Ruiz, Rubén, 2009. "Cooperative metaheuristics for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 193(2), pages 365-376, March.
  5. Naderi, Bahman & Ruiz, Rubén, 2014. "A scatter search algorithm for the distributed permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 239(2), pages 323-334.
  6. Ruiz, Ruben & Stutzle, Thomas, 2007. "A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 2033-2049, March.
  7. M. H. Alavidoost & Mosahar Tarimoradi & M. H. Fazel Zarandi, 2018. "Bi-objective mixed-integer nonlinear programming for multi-commodity tri-echelon supply chain networks," Journal of Intelligent Manufacturing, Springer, vol. 29(4), pages 809-826, April.
  8. Pan, Quan-Ke & Wang, Ling, 2012. "Effective heuristics for the blocking flowshop scheduling problem with makespan minimization," Omega, Elsevier, vol. 40(2), pages 218-229, April.
  9. Pan, Quan-Ke & Ruiz, Rubén, 2012. "An estimation of distribution algorithm for lot-streaming flow shop problems with setup times," Omega, Elsevier, vol. 40(2), pages 166-180, April.
  10. 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.
  11. Martín Ravetti & Carlos Riveros & Alexandre Mendes & Mauricio Resende & Panos Pardalos, 2012. "Parallel hybrid heuristics for the permutation flow shop problem," Annals of Operations Research, Springer, vol. 199(1), pages 269-284, October.
  12. 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.
  13. Mohd Nor Akmal Khalid & Umi Kalsom Yusof, 2021. "Incorporating shifting bottleneck identification in assembly line balancing problem using an artificial immune system approach," Flexible Services and Manufacturing Journal, Springer, vol. 33(3), pages 717-749, September.
  14. Martin, Clarence H, 2009. "A hybrid genetic algorithm/mathematical programming approach to the multi-family flowshop scheduling problem with lot streaming," Omega, Elsevier, vol. 37(1), pages 126-137, February.
  15. Vallada, Eva & Ruiz, Rubén, 2011. "A genetic algorithm for the unrelated parallel machine scheduling problem with sequence dependent setup times," European Journal of Operational Research, Elsevier, vol. 211(3), pages 612-622, June.
  16. Mohammad Saeid Atabaki & Mohammad Mohammadi & Bahman Naderi, 2017. "Hybrid Genetic Algorithm and Invasive Weed Optimization via Priority Based Encoding for Location-Allocation Decisions in a Three-Stage Supply Chain," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(02), pages 1-44, April.
  17. Naderi, B. & Zandieh, M., 2014. "Modeling and scheduling no-wait open shop problems," International Journal of Production Economics, Elsevier, vol. 158(C), pages 256-266.
  18. Angel A. Juan & Helena Ramalhinho-Lourenço & Manuel Mateo & Quim Castellà & Barry B. Barrios, 2012. "ILS-ESP: An efficient, simple, and parameter-free algorithm for solving the permutation flow-shop problem," Economics Working Papers 1319, Department of Economics and Business, Universitat Pompeu Fabra.
  19. 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.
  20. Pan, Quan-Ke & Ruiz, Rubén, 2014. "An effective iterated greedy algorithm for the mixed no-idle permutation flowshop scheduling problem," Omega, Elsevier, vol. 44(C), pages 41-50.
  21. Ronghua Meng & Yunqing Rao & Qiang Luo, 2020. "Modeling and solving for bi-objective cutting parallel machine scheduling problem," Annals of Operations Research, Springer, vol. 285(1), pages 223-245, February.
  22. Yenisey, Mehmet Mutlu & Yagmahan, Betul, 2014. "Multi-objective permutation flow shop scheduling problem: Literature review, classification and current trends," Omega, Elsevier, vol. 45(C), pages 119-135.
  23. 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.
  24. Liang, Wen-Yau & Huang, Chun-Che, 2008. "A hybrid approach to constrained evolutionary computing: Case of product synthesis," Omega, Elsevier, vol. 36(6), pages 1072-1085, December.
  25. Mosahar Tarimoradi & M. H. Fazel Zarandi & Hosain Zaman & I. B. Turksan, 2017. "Evolutionary fuzzy intelligent system for multi-objective supply chain network designs: an agent-based optimization state of the art," Journal of Intelligent Manufacturing, Springer, vol. 28(7), pages 1551-1579, October.
  26. Liu, Weihua & Liang, Zhicheng & Ye, Zi & Liu, Liang, 2016. "The optimal decision of customer order decoupling point for order insertion scheduling in logistics service supply chain," International Journal of Production Economics, Elsevier, vol. 175(C), pages 50-60.
  27. Vallada, Eva & Ruiz, Rubén & Framinan, Jose M., 2015. "New hard benchmark for flowshop scheduling problems minimising makespan," European Journal of Operational Research, Elsevier, vol. 240(3), pages 666-677.
  28. M. H. Alavidoost & M. H. Fazel Zarandi & Mosahar Tarimoradi & Yaser Nemati, 2017. "Modified genetic algorithm for simple straight and U-shaped assembly line balancing with fuzzy processing times," Journal of Intelligent Manufacturing, Springer, vol. 28(2), pages 313-336, February.
  29. Ławrynowicz Anna, 2011. "Genetic Algorithms for Solving Scheduling Problems in Manufacturing Systems," Foundations of Management, Sciendo, vol. 3(2), pages 7-26, January.
  30. Rad, Shahriar Farahmand & Ruiz, Rubén & Boroojerdian, Naser, 2009. "New high performing heuristics for minimizing makespan in permutation flowshops," Omega, Elsevier, vol. 37(2), pages 331-345, April.
  31. 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.
  32. Vallada, Eva & Ruiz, Rubén, 2010. "Genetic algorithms with path relinking for the minimum tardiness permutation flowshop problem," Omega, Elsevier, vol. 38(1-2), pages 57-67, February.
  33. 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.
  34. Gmys, Jan & Mezmaz, Mohand & Melab, Nouredine & Tuyttens, Daniel, 2020. "A computationally efficient Branch-and-Bound algorithm for the permutation flow-shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 284(3), pages 814-833.
  35. Pessoa, Luciana S. & Andrade, Carlos E., 2018. "Heuristics for a flowshop scheduling problem with stepwise job objective function," European Journal of Operational Research, Elsevier, vol. 266(3), pages 950-962.
  36. 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.
  37. Barry B. & Quim Castellà & Angel A. & Helena Ramalhinho Lourenco & Manuel Mateo, 2012. "ILS-ESP: An Efficient, Simple, and Parameter-Free Algorithm for Solving the Permutation Flow-Shop Problem," Working Papers 636, Barcelona School of Economics.
  38. Samavati, Mehran & Essam, Daryl & Nehring, Micah & Sarker, Ruhul, 2018. "A new methodology for the open-pit mine production scheduling problem," Omega, Elsevier, vol. 81(C), pages 169-182.
  39. Carlier, Jacques & Haouari, Mohamed & Kharbeche, Mohamed & Moukrim, Aziz, 2010. "An optimization-based heuristic for the robotic cell problem," European Journal of Operational Research, Elsevier, vol. 202(3), pages 636-645, May.
  40. Xiong, Fuli & Xing, Keyi & Wang, Feng, 2015. "Scheduling a hybrid assembly-differentiation flowshop to minimize total flow time," European Journal of Operational Research, Elsevier, vol. 240(2), pages 338-354.
  41. Sachchida Nand Chaurasia & Shyam Sundar & Alok Singh, 2017. "Hybrid metaheuristic approaches for the single machine total stepwise tardiness problem with release dates," Operational Research, Springer, vol. 17(1), pages 275-295, April.
  42. Shabtay, Dvir & Arviv, Kfir & Stern, Helman & Edan, Yael, 2014. "A combined robot selection and scheduling problem for flow-shops with no-wait restrictions," Omega, Elsevier, vol. 43(C), pages 96-107.
  43. Shen, Jiayu & Shi, Yuanji & Shi, Jianxin & Dai, Yunzhong & Li, Wei, 2023. "An uncertain permutation flow shop predictive scheduling problem with processing interruption," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
  44. Chung, Ji-Won & Oh, Seog-Moon & Choi, In-Chan, 2009. "A hybrid genetic algorithm for train sequencing in the Korean railway," Omega, Elsevier, vol. 37(3), pages 555-565, June.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.