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A Krill Herd algorithm for the multiobjective energy reduction multi-depot vehicle routing problem

Rapanaki Emmanouela, Psychas Iraklis-Dimitrios, Marinaki Magdalini, Matsatsinis Nikolaos, Marinakis Ioannis

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URIhttp://purl.tuc.gr/dl/dias/86DFAAA3-2078-419E-87AF-B63EF2CB602F-
Identifierhttps://doi.org/10.1007/978-3-030-64583-0_39-
Identifierhttps://link.springer.com/chapter/10.1007/978-3-030-64583-0_39-
Languageen-
Extent14 pagesen
TitleA Krill Herd algorithm for the multiobjective energy reduction multi-depot vehicle routing problemen
CreatorRapanaki Emmanouelaen
CreatorΡαπανακη Εμμανουελαel
CreatorPsychas Iraklis-Dimitriosen
CreatorΨυχας Ηρακλης-Δημητριοςel
CreatorMarinaki Magdalinien
CreatorΜαρινακη Μαγδαληνηel
CreatorMatsatsinis Nikolaosen
CreatorΜατσατσινης Νικολαοςel
CreatorMarinakis Ioannisen
CreatorΜαρινακης Ιωαννηςel
PublisherSpringer Natureen
Content SummaryKrill Herd algorithm is a powerful and relatively new Swarm Intelligence Algorithm that has been applied in a number of different kind of optimization problems since the time that it was published. In recent years there is a growing number of optimization models that are trying to reduce the energy consumption in routing problems. In this paper, a new variant of Krill Herd algorithm, the Parallel Multi-Start Non-dominated Sorting Krill Herd algorithm (PMS-KH), is proposed for the solution of a Vehicle Routing Problem variant, the Multiobjective Energy Reduction Multi-Depot Vehicle Routing Problem (MERMDVRP). Four different models are proposed where the distances between the customers and between the customers and the depots are either symmetric or asymmetric and the customers have either demand or pickup. The algorithm is compared with four other multiobjective algorithms, the Parallel Multi-Start Non-dominated Sorting Artificial Bee Colony (PMS-ABC), the Parallel Multi-Start Non-dominated Sorting Differential Evolution (PMS-NSDE), the Parallel Multi-Start Non-dominated Sorting Particle Swarm Optimization (PMS-NSPSO) and the Parallel Multi-Start Non-dominated Sorting Genetic Algorithm II (PMS-NSGA II) in a number of benchmark instances, giving very satisfactory results.en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2022-05-10-
Date of Publication2020-
SubjectVehicle routing problemen
SubjectKrill Herden
SubjectNSGA IIen
SubjectDEen
SubjectPSOen
SubjectABCen
SubjectVNSen
Bibliographic CitationE. Rapanaki, I.-D. Psychas, M. Marinaki, N. Matsatsinis, and Y. Marinakis, “A Krill Herd algorithm for the multiobjective energy reduction multi-depot vehicle routing problem,” in Machine Learning, Optimization, and Data Science, vol 12565, Lecture Notes in Computer Science, Cham, Switzerland: Springer Nature, 2020, pp. 434–447, doi: 10.1007/978-3-030-64583-0_39.en

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