Evolutionary optimisation of noisy multi-objective problems using confidence-based dynamic resampling
Author
Abstract
Suggested Citation
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Tan, K.C. & Cheong, C.Y. & Goh, C.K., 2007. "Solving multiobjective vehicle routing problem with stochastic demand via evolutionary computation," European Journal of Operational Research, Elsevier, vol. 177(2), pages 813-839, March.
- Lee, Loo Hay & Chew, Ek Peng & Teng, Suyan & Chen, Yankai, 2008. "Multi-objective simulation-based evolutionary algorithm for an aircraft spare parts allocation problem," European Journal of Operational Research, Elsevier, vol. 189(2), pages 476-491, September.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Cruz-Ramı´rez, Manuel & Hervás-Martı´nez, César & Fernández, Juan Carlos & Briceño, Javier & de la Mata, Manuel, 2012. "Multi-objective evolutionary algorithm for donor–recipient decision system in liver transplants," European Journal of Operational Research, Elsevier, vol. 222(2), pages 317-327.
- Hossein Karshenas & Concha Bielza & Pedro Larrañaga, 2015. "Interval-based ranking in noisy evolutionary multi-objective optimization," Computational Optimization and Applications, Springer, vol. 61(2), pages 517-555, June.
- Rojas Gonzalez, Sebastian & Jalali, Hamed & Van Nieuwenhuyse, Inneke, 2020. "A multiobjective stochastic simulation optimization algorithm," European Journal of Operational Research, Elsevier, vol. 284(1), pages 212-226.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Goh, C.K. & Tan, K.C. & Liu, D.S. & Chiam, S.C., 2010. "A competitive and cooperative co-evolutionary approach to multi-objective particle swarm optimization algorithm design," European Journal of Operational Research, Elsevier, vol. 202(1), pages 42-54, April.
- Joaquín Pacheco & Rafael Caballero & Manuel Laguna & Julián Molina, 2013. "Bi-Objective Bus Routing: An Application to School Buses in Rural Areas," Transportation Science, INFORMS, vol. 47(3), pages 397-411, August.
- Jorge Oyola & Halvard Arntzen & David L. Woodruff, 2017. "The stochastic vehicle routing problem, a literature review, Part II: solution methods," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(4), pages 349-388, December.
- Lin, Rung-Chuan & Sir, Mustafa Y. & Pasupathy, Kalyan S., 2013. "Multi-objective simulation optimization using data envelopment analysis and genetic algorithm: Specific application to determining optimal resource levels in surgical services," Omega, Elsevier, vol. 41(5), pages 881-892.
- C. Y. Lam, 2021. "Optimizing logistics routings in a network perspective of supply and demand nodes," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(1), pages 357-377, March.
- Alexandre M. Florio & Richard F. Hartl & Stefan Minner & Juan-José Salazar-González, 2021. "A Branch-and-Price Algorithm for the Vehicle Routing Problem with Stochastic Demands and Probabilistic Duration Constraints," Transportation Science, INFORMS, vol. 55(1), pages 122-138, 1-2.
- Miranda, Rafael de Carvalho & Montevechi, José Arnaldo Barra & da Silva, Aneirson Francisco & Marins, Fernando Augusto Silva, 2017. "Increasing the efficiency in integer simulation optimization: Reducing the search space through data envelopment analysis and orthogonal arrays," European Journal of Operational Research, Elsevier, vol. 262(2), pages 673-681.
- Lulu Cheng & Ning Zhao & Kan Wu, 2024. "Stochastic Multi-Objective Multi-Trip AMR Routing Problem with Time Windows," Mathematics, MDPI, vol. 12(15), pages 1-20, July.
- Yunyun Niu & Zehua Yang & Rong Wen & Jianhua Xiao & Shuai Zhang, 2022. "Solving the Green Open Vehicle Routing Problem Using a Membrane-Inspired Hybrid Algorithm," Sustainability, MDPI, vol. 14(14), pages 1-22, July.
- Min, Xinyuan & Sok, Jaap & de Zwart, Feije & Oude Lansink, Alfons, 2024. "Multi-stakeholder multi-objective greenhouse design optimization," Agricultural Systems, Elsevier, vol. 215(C).
- Zhang, Zizhen & Che, Oscar & Cheang, Brenda & Lim, Andrew & Qin, Hu, 2013. "A memetic algorithm for the multiperiod vehicle routing problem with profit," European Journal of Operational Research, Elsevier, vol. 229(3), pages 573-584.
- Ito, Kodo & Mizutani, Satoshi & Nakagawa, Toshio, 2020. "Optimal inspection models with minimal repair," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
- Joshua Q. Hale & Helin Zhu & Enlu Zhou, 2020. "Domination Measure: A New Metric for Solving Multiobjective Optimization," INFORMS Journal on Computing, INFORMS, vol. 32(3), pages 565-581, July.
- Seyedmehdi Mirmohammadsadeghi & Shamsuddin Ahmed, 2015. "Memetic Heuristic Approach for Solving Truck and Trailer Routing Problems with Stochastic Demands and Time Windows," Networks and Spatial Economics, Springer, vol. 15(4), pages 1093-1115, December.
- Hu, Qiwei & Boylan, John E. & Chen, Huijing & Labib, Ashraf, 2018. "OR in spare parts management: A review," European Journal of Operational Research, Elsevier, vol. 266(2), pages 395-414.
- C. Cheong & K. Tan & D. Liu & C. Lin, 2010. "Multi-objective and prioritized berth allocation in container ports," Annals of Operations Research, Springer, vol. 180(1), pages 63-103, November.
- Spliet, R. & Gabor, A.F. & Dekker, R., 2009. "The Vehicle Rescheduling Problem," Econometric Institute Research Papers EI 2009-43, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Wang, Yujia & Yang, Yupu, 2010. "Particle swarm with equilibrium strategy of selection for multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 200(1), pages 187-197, January.
- 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.
- S. F. Ghannadpour & S. Noori & R. Tavakkoli-Moghaddam, 2014. "A multi-objective vehicle routing and scheduling problem with uncertainty in customers’ request and priority," Journal of Combinatorial Optimization, Springer, vol. 28(2), pages 414-446, August.
More about this item
Keywords
Evolutionary computations Multi-objective optimisation Noise Simulation;Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:204:y:2010:i:3:p:533-544. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.