4.6 Article

Extension of Particle Swarm Optimization algorithm for solving two-level time minimization transportation problem

期刊

MATHEMATICS AND COMPUTERS IN SIMULATION
卷 204, 期 -, 页码 727-742

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ELSEVIER
DOI: 10.1016/j.matcom.2022.09.013

关键词

Swarm intelligence; Particle Swarm Optimization; Time minimization transportation problem; Optimal solution

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This paper addresses a two-level time minimization transportation problem and proposes a solution procedure that hybridizes new algorithms within the Particle Swarm Optimization to efficiently utilize resources. The procedure eliminates the rigid constraints imposed by traditional techniques and provides a systematic approach.
A time minimization transportation problem deals with the resource efficiency to minimize time taken by the transport systems to deliver the commodity from sources to destinations. In this paper, a two-level time minimization transportation problem has been considered that categorizes the source-destination links into Level-I and Level-II with respect to the higher and lower level priority. The optimal delivery schedule of Level-I is followed up with the same for the Level-II cells. The paper proposes a solution procedure consisting of new algorithms that have been hybridized within the Particle Swarm Optimization to solve the problem making efficient use of resources. The solution procedure provides a methodical approach to the transport enterprises.This procedure does away with the rigid constraints, such as the location and number of non-zero allocations, required to be met by the traditional techniques of solving the transportation problem. The procedure generates pairs of Level-I and Level-II times at each iteration and the best pair(s) amongst these is/are marked out as the optimal solution of the problem. The solution procedure is explained through a numerical illustration.(c) 2022 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.

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