A hybrid multi-objective evolutionary algorithm for solving truck and trailer vehicle routing problems

This paper considers a transportation problem for moving empty or laden containers for a logistic company. Owing to the limited resource of its vehicles (trucks and trailers), the company often needs to sub-contract certain job orders to outsourced companies. A model for this truck and trailer vehic...

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Veröffentlicht in:	European journal of operational research Jg. 172; H. 3; S. 855 - 885
Hauptverfasser:	Tan, K.C., Chew, Y.H., Lee, L.H.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.08.2006 Elsevier Elsevier Sequoia S.A
Schriftenreihe:	European Journal of Operational Research
Schlagworte:	Algorithms Applied sciences Decision theory. Utility theory Evolutionary algorithms Exact sciences and technology Flows in networks. Combinatorial problems Genetic algorithms Heuristic Job orders Logistics Multi-objective optimization Operational research and scientific management Operational research. Management science Operations research Optimization Route optimization Studies Transportation problem (Operations research) Trucks Vehicle routing Vehicles Vehicle routing Multi-objective optimization Evolutionary algorithms Local search Pareto optimum Decision support system Decision making Evolutionary algorithm Vehicle routing problem Multiobjective programming Combinatorial optimization Optimization Container Transportation problem Time window Minimal distance Logistics
ISSN:	0377-2217, 1872-6860
Online-Zugang:	Volltext
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