In this paper, a fitness landscape analysis of a complex Vehicle Routing Problem (VRP) is presented, and the effectiveness of population-based heuristic techniques is analyzed on this complex problem. The Vehicle Routing Problem is a common optimization task where vehicles deliver products to customers. The task is NP difficult; several heuristic algorithms have been involved in solving the problem. The objective is to select the right algorithm for the task, where the search space analysis provides an analytical answer. In this paper, the analysis of the population-based heuristics is presented. The paper presents an analysis of the following population algorithms: Ant System, Elitist Strategy of Ant System, Firefly Algorithm, Genetic Algorithm. In this paper, the results of the iterations of each population algorithm are analyzed in terms of the followings: fitness values, fitness distances, basic swap sequence distances, Hamming distances, the best solution, and filtered optima. Based on the test results, it can be concluded that the Ant System algorithm proved to be the most effective and the Firefly algorithm is not recommended to solve the presented complicated VRP.


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    Title :

    Fitness Landscape Analysis of Population-Based Heuristics in Solving a Complex Vehicle Routing Problem


    Additional title:

    Lect.Notes Mechanical Engineering


    Contributors:

    Conference:

    Vehicle and Automotive Engineering ; 2022 ; MISKOLC, Hungary September 08, 2022 - September 09, 2022



    Publication date :

    2022-09-10


    Size :

    11 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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