An Iterated Local Search for the Split Delivery Vehicle Routing Problem

Wen, Zheng; Dong, Xianguang; Han, Sangyong

doi:10.2991/cisia-15.2015.12

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…The experimental results indicated the feasibility of the algorithm. Wen [16] presented a three-stage local-search algorithm. First, GENIUS was adopted to solve the TSP path for the whole customer domain; all points in the path were partitioned into groups based on the vehicle capacity.…”

Section: Introductionmentioning

confidence: 99%

Split-Delivery Vehicle Routing Problems Based on a Multi-Restart Improved Sweep Approach

Min¹,

Jin²,

Lu³

2019

Int. j. simul. model.

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The vehicle routing problem (VRP) with split delivery is an important branch of the classic VRP. The objective is to reduce the transportation distance and number of vehicles used. This study proposes a two-stage algorithm based on an improved sweep heuristic approach to solve this problem. We cluster customer points into a minimum number of groups through a multi-restart-iteration sweeping algorithm (MRISA). The load demands and split point in each group are fine-adjusted using the load rate and threshold coefficient. To reduce the travel distance in each group, an optimal route is produced by a tabu search algorithm (TSA). The computational simulation results demonstrate that the proposed method in this study is feasible and efficient, and the near-optimal performance of the proposed method is achieved regarding the transportation distance and computation time to the instances with a scattered distribution geographical characteristic; however, the strategy of "the maximum-minimum distance clustering first, and MRISA + TSA executing later" is much more useful for instances with a clustered-distribution geographical characteristic.

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Section: Introductionmentioning

confidence: 99%

Split-Delivery Vehicle Routing Problems Based on a Multi-Restart Improved Sweep Approach

Min¹,

Jin²,

Lu³

2019

Int. j. simul. model.

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“…As has been mentioned in the introduction, route planning is a hot topic inside artificial intelligence. The different problems arisen in this field produce a huge amount of works annually in both international conferences [11,12], and journals [13,14,15]. In addition, they inspire the edition of several technical reports [16], and scientific books [17,18].…”

Section: Introductionmentioning

confidence: 99%

Good practice proposal for the implementation, presentation, and comparison of metaheuristics for solving routing problems

et al. 2018

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Researchers who investigate in any area related to computational algorithms (both defining new algorithms or improving existing ones) usually find large difficulties to test their work. Comparisons among different researches in this field are often a hard task, due to the ambiguity or lack of detail in the presentation of the work and its results. On many occasions, the replication of the work conducted by other researchers is required, which leads to a waste of time and a delay in the research advances. The authors of this study propose a procedure to introduce new techniques and their results in the field of routing problems. In this paper this procedure is detailed, and a set of good practices to follow are deeply described. It is noteworthy that this procedure can be applied to any combinatorial optimization problem. Anyway, the literature of this study is focused on routing problems. This field has been chosen because of its importance in real world, and its relevance in the actual literature.

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“…Problems arisen in this field are usually known as the so-called vehicle routing problems, which are a particular case of problems within combinatorial optimization. Different sorts of VRPs can lead to lots of research work annually in international conferences [1,2], journals [3,4,5], technical reports [6] and edited books [7,8].…”

Section: Introductionmentioning

confidence: 99%

An Evolutionary Discrete Firefly Algorithm with Novel Operators for Solving the Vehicle Routing Problem with Time Windows

Osaba

Carballedo

Yang

et al. 2016

Studies in Computational Intelligence

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An evolutionary discrete version of the Firefly Algorithm (EDFA) is presented in this chapter for solving the well-known Vehicle Routing Problem with Time Windows (VRPTW). The contribution of this work is not only the adaptation of the EDFA to the VRPTW, but also with some novel route optimization operators. These operators incorporate the process of minimizing the number of routes for a solution in the search process where node selective extractions and subsequent reinsertion are performed. The new operators analyze all routes of the current solution and thus increase the diversification capacity of the search process (in contrast with the traditional node and arc exchange based operators). With the aim of proving that the proposed EDFA and operators are effective, some different versions of the EDFA are compared. The present work includes the experimentation with all the 56 instances of the well-known VRPTW set. In order to obtain rigorous and fair conclusions, two different statistical tests have been conducted.

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An Iterated Local Search for the Split Delivery Vehicle Routing Problem

Cited by 5 publications

References 11 publications

Split-Delivery Vehicle Routing Problems Based on a Multi-Restart Improved Sweep Approach

Split-Delivery Vehicle Routing Problems Based on a Multi-Restart Improved Sweep Approach

Good practice proposal for the implementation, presentation, and comparison of metaheuristics for solving routing problems

An Evolutionary Discrete Firefly Algorithm with Novel Operators for Solving the Vehicle Routing Problem with Time Windows

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