Literature DB >> 35052079

Constrained Fitness Landscape Analysis of Capacitated Vehicle Routing Problems.

Sebastián Muñoz-Herrera1,2, Karol Suchan3,4.   

Abstract

Vehicle Routing Problems (VRP) comprise many variants obtained by adding to the original problem constraints representing diverse system characteristics. Different variants are widely studied in the literature; however, the impact that these constraints have on the structure of the search space associated with the problem is unknown, and so is their influence on the performance of search algorithms used to solve it. This article explores how assignation constraints (such as a limited vehicle capacity) impact VRP by disturbing the network structure defined by the solution space and the local operators in use. This research focuses on Fitness Landscape Analysis for the multiple Traveling Salesman Problem (m-TSP) and Capacitated VRP (CVRP). We propose a new Fitness Landscape Analysis measure that provides valuable information to characterize the fitness landscape's structure under specific scenarios and obtain several relationships between the fitness landscape's structure and the algorithmic performance.

Entities:  

Keywords:  Fitness Landscape Analysis; Multinomial Logistic Regression; Principal Component Analysis; feasibility analysis; information analysis; statistical analysis; vehicle routing problem

Year:  2021        PMID: 35052079      PMCID: PMC8775137          DOI: 10.3390/e24010053

Source DB:  PubMed          Journal:  Entropy (Basel)        ISSN: 1099-4300            Impact factor:   2.524


  3 in total

1.  Information characteristics and the structure of landscapes.

Authors:  V K Vassilev; T C Fogarty; J F Miller
Journal:  Evol Comput       Date:  2000       Impact factor: 3.277

2.  Anisotropy in fitness landscapes.

Authors:  P F Stadler; W Grüner
Journal:  J Theor Biol       Date:  1993-12-07       Impact factor: 2.691

3.  An Analysis of the Fitness Landscape of Travelling Salesman Problem.

Authors:  Mohammad-H Tayarani-N; Adam Prügel-Bennett
Journal:  Evol Comput       Date:  2015-06-12       Impact factor: 3.277

  3 in total

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