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Titlebook: Bio-inspired Algorithms for the Vehicle Routing Problem; Francisco Babtista Pereira,Jorge Tavares Book 2009 Springer-Verlag Berlin Heidelb

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期刊全称Bio-inspired Algorithms for the Vehicle Routing Problem
影响因子2023Francisco Babtista Pereira,Jorge Tavares
视频video
发行地址Comprehensive review of the most relevant bio-inspired approaches to different Vehicle Routing Problem variants
学科分类Studies in Computational Intelligence
图书封面Titlebook: Bio-inspired Algorithms for the Vehicle Routing Problem;  Francisco Babtista Pereira,Jorge Tavares Book 2009 Springer-Verlag Berlin Heidelb
影响因子The vehicle routing problem (VRP) is one of the most famous combinatorial optimization problems. In simple terms, the goal is to determine a set of routes with overall minimum cost that can satisfy several geographical scattered - mands. A ?eet of vehicles located in one or more depots is available to ful?ll the requests. A large number of variants exist, adding di?erent constraints to the original de?nition. Some examples are related to the number of depots, the ordering for visiting the customers or to time windows specifying a desirable period to arrive to a given location. The original version of this problem was proposed by Dantzig and Ramser in 1959 [1]. In their seminal paper, the authors address the calculation of a set of optimal routes for a ?eet of gasoline delivery trucks. Since then, the VRP has attractedtheattentionofalargenumberofresearchers.Aconsiderablepartofits success is a consequence of its practical interest, as it resembles many real-world problems faced everyday by distribution and transportation companies, just to mention a few applications areas. In this context, the development of e?cient optimization techniques is crucial. They are able to provide new and
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Hybridizing Problem-Specific Operators with Meta-heuristics for Solving the Multi-objective Vehiclek, a few problem-specific operators, including two search operators for local exploitation and the route simulation method (RSM) for evaluating solution quality, were proposed and incorporated with a multi-objective evolutionary algorithm (MOEA). In this chapter, the operators are hybridized with se
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A Memetic Algorithm for a Pick-Up and Delivery Problem by Helicopter,in a set of oil platforms by one helicopter that may have to undertake several routes in sequence. Different versions of the algorithm are presented and tested on randomly generated instances as well as on real instances provided by a petroleum company. The results show that the solutions obtained a
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https://doi.org/10.1007/978-1-349-17893-3oblems, where least-cost collection or delivery routes are designed to serve a set of customers in a transportation network. From a methodological standpoint, the review includes evolutionary algorithms, ant colony optimization, particle swarm optimization, neural networks, artificial immune systems
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