Abstract
In the distribution of goods to final customers, interrelated decisions have to be made, such as the location of the collection points for the goods, the routes served from the central warehouse and the allocation of customers to the collection points. The problem becomes even more complex when several decision makers are involved and multiple objectives should be taken into consideration. This paper addresses a vehicle routing problem in which customers are allowed to select the location in which they want to receive their goods among those made available by the distribution company. The aim of this company is to minimize the total cost of serving the routes as well as to satisfy customers. A bilevel biobjective problem with multiple followers is proposed to model this hierarchical supply chain. The upper level decision maker is the distribution company which decides on the locations made available and the routes which are used to serve these locations. Each customer plays the role of a follower and decides where to collect his/her goods. An evolutionary algorithm involving the solution of several optimization problems is developed for approaching the Pareto front, whose performance is assessed in a computational experiment.
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References
Affenzeller M, Wagner S, Winkler S, Beham A (2009) Genetic algorithms and genetic programming: modern concepts and practical applications. Chapman and Hall/CRC
Baldacci R, Dell’Amico M, Salazar González JJ (2007) The capacitated \(m\)-ring-star problem. Oper Res 55(6):1147–1162
Calvete HI, Galé C (2007) Linear bilevel multi-follower programming with independent followers. J Global Optim 39(3):409–417
Calvete HI, Galé C, Iranzo JA (2011) Planning of a decentralized distribution network using bilevel optimization. Comput Oper Res 38(1):320–327
Calvete HI, Galé C, Oliveros MJ (2011) Bilevel model for production-distribution planning solved by using ant colony optimization. Comput Oper Res 38(1):320–327
Cao D, Chen M (2006) Capacitated plant selection in a decentralized manufacturing environment: a bilevel optimization approach. Eur J Oper Res 169(1):97–110
Chion R, Weise T, Michalewicz Z (eds) (2012) Variants of evolutionary algorithms for real-world applications. Springer, Berlin
Coello CA (2017) Recent results and open problems in evolutionary multiobjective optimization. In: Lecture notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). LNCS:3–21, p 10687
Deb K, Pratap A, Agrawal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6:182–197
Dempe S (2018) Bilevel optimization: theory, algorithms and applications. Preprint 2018-11, Fakultät für Mathematik und Informatik, TU Bergakademie Freiberg
Ehrgott M (2005) Multicriteria optimization, 2nd edn. Springer, Heildeberg
Huang B, Liu N (1894) Bilevel programming approach to optimizing a logistic distribution network with balancing requirements. Transp Res Record J Transp Res Board 188–197:2004
Marinakis Y, Marinaki M (2008) A bilevel genetic algorithm for a real life location routing problem. Int J Logistics Res Appl 11(1):49–65
Zitzler E, Kunzli S (2004) Indicator-based selection in multiobjective search. In: Yao X, Burke E, Lozano JA, Smith J, Merelo-Guervós JJ, Bullinaria JA, Rowe J, Tiño P, Kabán A, Schwefel HP (eds) Eight international conference on parallel Problem Solving from Nature (PPSN VIII). Lecture notes in computer science, vol 3242. Springer, Berlin, pp 832–842
Acknowledgments
This research work has been funded by the Spanish Ministry of Economy, Industry and Competitiveness under grant ECO2016-76567-C4-3-R and by the Gobierno de Aragón under grant E41_17R (FEDER 2014–2020 “Construyendo Europa desde Aragón”).
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Calvete, H.I., Galé, C., Iranzo, J.A. (2021). An Evolutionary Algorithm for a Bilevel Biobjective Location-Routing-Allocation Problem. In: Gaspar-Cunha, A., Periaux, J., Giannakoglou, K.C., Gauger, N.R., Quagliarella, D., Greiner, D. (eds) Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences. Computational Methods in Applied Sciences, vol 55. Springer, Cham. https://doi.org/10.1007/978-3-030-57422-2_2
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DOI: https://doi.org/10.1007/978-3-030-57422-2_2
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