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A Robust Genetic Algorithm for Resource Allocation in Project Scheduling

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Cited by:

  1. C-C Chang & R-S Chen, 2007. "Project advancement and its applications to multi-air-route quality budget allocation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(8), pages 1008-1020, August.
  2. Zamani, Reza, 2013. "A competitive magnet-based genetic algorithm for solving the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 229(2), pages 552-559.
  3. Bernardo F. Almeida & Isabel Correia & Francisco Saldanha-da-Gama, 2018. "A biased random-key genetic algorithm for the project scheduling problem with flexible resources," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(2), pages 283-308, July.
  4. Valls, Vicente & Ballestin, Francisco & Quintanilla, Sacramento, 2005. "Justification and RCPSP: A technique that pays," European Journal of Operational Research, Elsevier, vol. 165(2), pages 375-386, September.
  5. Feifei Li & Zhe Xu, 2018. "A multi-agent system for distributed multi-project scheduling with two-stage decomposition," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-24, October.
  6. Kemmoé Tchomté, Sylverin & Gourgand, Michel, 2009. "Particle swarm optimization: A study of particle displacement for solving continuous and combinatorial optimization problems," International Journal of Production Economics, Elsevier, vol. 121(1), pages 57-67, September.
  7. Sherali, Hanif D. & Van Goubergen, Dirk & Van Landeghem, Hendrik, 2008. "A quantitative approach for scheduling activities to reduce set-up in multiple machine lines," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1224-1237, June.
  8. Majid Askarifard & Hamidreza Abbasianjahromi & Mehran Sepehri & Ehsanollah Zeighami, 2021. "A robust multi-objective optimization model for project scheduling considering risk and sustainable development criteria," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 11494-11524, August.
  9. D. Debels & M. Vanhoucke, 2005. "A Bi-Population Based Genetic Algorithm for the Resource-Constrained Project Scheduling Problem," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/294, Ghent University, Faculty of Economics and Business Administration.
  10. Bogumiła Krzeszowska, 2013. "Three step procedure for a multiple criteria problem of project portfolio scheduling," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 23(4), pages 55-74.
  11. Abdollah Arasteh, 2020. "Considering Project Management Activities for Engineering Design Groups," SN Operations Research Forum, Springer, vol. 1(4), pages 1-29, December.
  12. Debels, Dieter & De Reyck, Bert & Leus, Roel & Vanhoucke, Mario, 2006. "A hybrid scatter search/electromagnetism meta-heuristic for project scheduling," European Journal of Operational Research, Elsevier, vol. 169(2), pages 638-653, March.
  13. Filipa Fernandes & Charalampos Stasinakis & Zivile Zekaite, 2019. "Forecasting government bond spreads with heuristic models: evidence from the Eurozone periphery," Annals of Operations Research, Springer, vol. 282(1), pages 87-118, November.
  14. Peteghem, Vincent Van & Vanhoucke, Mario, 2010. "A genetic algorithm for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 201(2), pages 409-418, March.
  15. Moumene, Khaled & Ferland, Jacques A., 2009. "Activity list representation for a generalization of the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 199(1), pages 46-54, November.
  16. Tseng, Lin-Yu & Chen, Shih-Chieh, 2006. "A hybrid metaheuristic for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 175(2), pages 707-721, December.
  17. Ruiz, Ruben & Maroto, Concepcion & Alcaraz, Javier, 2005. "Solving the flowshop scheduling problem with sequence dependent setup times using advanced metaheuristics," European Journal of Operational Research, Elsevier, vol. 165(1), pages 34-54, August.
  18. Dieter Debels & Mario Vanhoucke, 2007. "A Decomposition-Based Genetic Algorithm for the Resource-Constrained Project-Scheduling Problem," Operations Research, INFORMS, vol. 55(3), pages 457-469, June.
  19. Kolisch, Rainer & Hartmann, Sonke, 2006. "Experimental investigation of heuristics for resource-constrained project scheduling: An update," European Journal of Operational Research, Elsevier, vol. 174(1), pages 23-37, October.
  20. D. Debels & M. Vanhoucke, 2005. "A Decomposition-Based Heuristic For The Resource-Constrained Project Scheduling Problem," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/293, Ghent University, Faculty of Economics and Business Administration.
  21. Bouleimen, K. & Lecocq, H., 2003. "A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version," European Journal of Operational Research, Elsevier, vol. 149(2), pages 268-281, September.
  22. D. Debels & M. Vanhoucke, 2004. "An Electromagnetism Meta-Heuristic For The Resource-Constrained Project Scheduling Problem," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/251, Ghent University, Faculty of Economics and Business Administration.
  23. J Alcaraz & C Maroto & R Ruiz, 2003. "Solving the Multi-Mode Resource-Constrained Project Scheduling Problem with genetic algorithms," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(6), pages 614-626, June.
  24. Ranjbar, Mohammad & De Reyck, Bert & Kianfar, Fereydoon, 2009. "A hybrid scatter search for the discrete time/resource trade-off problem in project scheduling," European Journal of Operational Research, Elsevier, vol. 193(1), pages 35-48, February.
  25. Ruiz, Rubén & Maroto, Concepciøn & Alcaraz, Javier, 2006. "Two new robust genetic algorithms for the flowshop scheduling problem," Omega, Elsevier, vol. 34(5), pages 461-476, October.
  26. Aidin Delgoshaei & Timon Rabczuk & Ahad Ali & Mohd Khairol Anuar Ariffin, 2017. "An applicable method for modifying over-allocated multi-mode resource constraint schedules in the presence of preemptive resources," Annals of Operations Research, Springer, vol. 259(1), pages 85-117, December.
  27. Yang-Kuei Lin & Chin Soon Chong, 2017. "Fast GA-based project scheduling for computing resources allocation in a cloud manufacturing system," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1189-1201, June.
  28. Pei, Jun & Liu, Xinbao & Fan, Wenjuan & Pardalos, Panos M. & Lu, Shaojun, 2019. "A hybrid BA-VNS algorithm for coordinated serial-batching scheduling with deteriorating jobs, financial budget, and resource constraint in multiple manufacturers," Omega, Elsevier, vol. 82(C), pages 55-69.
  29. Valls, Vicente & Ballestin, Francisco & Quintanilla, Sacramento, 2008. "A hybrid genetic algorithm for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 185(2), pages 495-508, March.
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