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Genetic local search for multi-objective combinatorial optimization

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  1. Aymeric Blot & Marie-Éléonore Kessaci & Laetitia Jourdan, 2018. "Survey and unification of local search techniques in metaheuristics for multi-objective combinatorial optimisation," Journal of Heuristics, Springer, vol. 24(6), pages 853-877, December.
  2. Zhang, Rui & Chang, Pei-Chann & Wu, Cheng, 2013. "A hybrid genetic algorithm for the job shop scheduling problem with practical considerations for manufacturing costs: Investigations motivated by vehicle production," International Journal of Production Economics, Elsevier, vol. 145(1), pages 38-52.
  3. Chang, Tsung-Sheng & Yen, Hui-Mei, 2012. "City-courier routing and scheduling problems," European Journal of Operational Research, Elsevier, vol. 223(2), pages 489-498.
  4. 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.
  5. Eduardo Segredo & Carlos Segura & Coromoto León, 2014. "Memetic algorithms and hyperheuristics applied to a multiobjectivised two-dimensional packing problem," Journal of Global Optimization, Springer, vol. 58(4), pages 769-794, April.
  6. Peter Bober, 2011. "Comparison of Different Approaches to the Cutting Plan Scheduling," Quality Innovation Prosperity, Technical University of Košice, Department of integrated management, vol. 15(1).
  7. Tadashi Yamada & Bona Frazila Russ & Jun Castro & Eiichi Taniguchi, 2009. "Designing Multimodal Freight Transport Networks: A Heuristic Approach and Applications," Transportation Science, INFORMS, vol. 43(2), pages 129-143, May.
  8. Lakmali Weerasena, 2022. "Advancing local search approximations for multiobjective combinatorial optimization problems," Journal of Combinatorial Optimization, Springer, vol. 43(3), pages 589-612, April.
  9. Chou, Jui-Sheng & Truong, Dinh-Nhat, 2020. "Multiobjective optimization inspired by behavior of jellyfish for solving structural design problems," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
  10. KIlIç, Murat & Ulusoy, Gündüz & Serifoglu, Funda Sivrikaya, 2008. "A bi-objective genetic algorithm approach to risk mitigation in project scheduling," International Journal of Production Economics, Elsevier, vol. 112(1), pages 202-216, March.
  11. Wang, Rui & Purshouse, Robin C. & Fleming, Peter J., 2015. "Preference-inspired co-evolutionary algorithms using weight vectors," European Journal of Operational Research, Elsevier, vol. 243(2), pages 423-441.
  12. Justus Bonz, 2021. "Application of a multi-objective multi traveling salesperson problem with time windows," Public Transport, Springer, vol. 13(1), pages 35-57, March.
  13. Aristotelis E. Thanos & Nurcin Celik & Juan P. Sáenz, 2016. "An Evolutionary Sequential Sampling Algorithm for Multi-Objective Optimization," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(01), pages 1-21, February.
  14. Lakmali Weerasena & Aniekan Ebiefung & Anthony Skjellum, 2022. "Design of a heuristic algorithm for the generalized multi-objective set covering problem," Computational Optimization and Applications, Springer, vol. 82(3), pages 717-751, July.
  15. Garcia-Martinez, C. & Cordon, O. & Herrera, F., 2007. "A taxonomy and an empirical analysis of multiple objective ant colony optimization algorithms for the bi-criteria TSP," European Journal of Operational Research, Elsevier, vol. 180(1), pages 116-148, July.
  16. Zouache, Djaafar & Moussaoui, Abdelouahab & Ben Abdelaziz, Fouad, 2018. "A cooperative swarm intelligence algorithm for multi-objective discrete optimization with application to the knapsack problem," European Journal of Operational Research, Elsevier, vol. 264(1), pages 74-88.
  17. Djaafar Zouache & Fouad Ben Abdelaziz & Mira Lefkir & Nour El-Houda Chalabi, 2021. "Guided Moth–Flame optimiser for multi-objective optimization problems," Annals of Operations Research, Springer, vol. 296(1), pages 877-899, January.
  18. Florios, Kostas & Mavrotas, George, 2014. "Generation of the exact Pareto set in multi-objective traveling salesman and set covering problems," MPRA Paper 105074, University Library of Munich, Germany.
  19. Ana Iannoni & Reinaldo Morabito & Cem Saydam, 2008. "A hypercube queueing model embedded into a genetic algorithm for ambulance deployment on highways," Annals of Operations Research, Springer, vol. 157(1), pages 207-224, January.
  20. Iannoni, Ana Paula & Morabito, Reinaldo & Saydam, Cem, 2009. "An optimization approach for ambulance location and the districting of the response segments on highways," European Journal of Operational Research, Elsevier, vol. 195(2), pages 528-542, June.
  21. Mei, Yi & Salim, Flora D. & Li, Xiaodong, 2016. "Efficient meta-heuristics for the Multi-Objective Time-Dependent Orienteering Problem," European Journal of Operational Research, Elsevier, vol. 254(2), pages 443-457.
  22. Sun, Mu-Xia & Li, Yan-Fu & Zio, Enrico, 2019. "On the optimal redundancy allocation for multi-state series–parallel systems under epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
  23. Ying Xu & Rong Qu & Renfa Li, 2013. "A simulated annealing based genetic local search algorithm for multi-objective multicast routing problems," Annals of Operations Research, Springer, vol. 206(1), pages 527-555, July.
  24. Ishibuchi, Hisao & Narukawa, Kaname & Tsukamoto, Noritaka & Nojima, Yusuke, 2008. "An empirical study on similarity-based mating for evolutionary multiobjective combinatorial optimization," European Journal of Operational Research, Elsevier, vol. 188(1), pages 57-75, July.
  25. Jaszkiewicz, Andrzej, 2018. "Many-Objective Pareto Local Search," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1001-1013.
  26. Luo, Hao & Yang, Xuan & Kong, Xiang T.R., 2019. "A synchronized production-warehouse management solution for reengineering the online-offline integrated order fulfillment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 211-230.
  27. Calvete, Herminia I. & Galé, Carmen & Iranzo, José A., 2016. "MEALS: A multiobjective evolutionary algorithm with local search for solving the bi-objective ring star problem," European Journal of Operational Research, Elsevier, vol. 250(2), pages 377-388.
  28. Bogdan Rębiasz, 2009. "A method for selecting an effective investment project portfolio," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 19(3), pages 95-117.
  29. Arroyo, Jose Elias Claudio & Armentano, Vinicius Amaral, 2005. "Genetic local search for multi-objective flowshop scheduling problems," European Journal of Operational Research, Elsevier, vol. 167(3), pages 717-738, December.
  30. Selçuklu, Saltuk Buğra & Coit, David W. & Felder, Frank A., 2020. "Pareto uncertainty index for evaluating and comparing solutions for stochastic multiple objective problems," European Journal of Operational Research, Elsevier, vol. 284(2), pages 644-659.
  31. Sato, Hiroyuki & Aguirre, Hernan E. & Tanaka, Kiyoshi, 2007. "Local dominance and local recombination in MOEAs on 0/1 multiobjective knapsack problems," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1708-1723, September.
  32. Burke, E.K. & Landa Silva, J.D., 2006. "The influence of the fitness evaluation method on the performance of multiobjective search algorithms," European Journal of Operational Research, Elsevier, vol. 169(3), pages 875-897, March.
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