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Route Optimization in logistics distribution based on Particle Swarm Optimization

by Appiah Martinson Yeboah, Xiong Qiang
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 178 - Number 30
Year of Publication: 2019
Authors: Appiah Martinson Yeboah, Xiong Qiang
10.5120/ijca2019919179

Appiah Martinson Yeboah, Xiong Qiang . Route Optimization in logistics distribution based on Particle Swarm Optimization. International Journal of Computer Applications. 178, 30 ( Jul 2019), 23-27. DOI=10.5120/ijca2019919179

@article{ 10.5120/ijca2019919179,
author = { Appiah Martinson Yeboah, Xiong Qiang },
title = { Route Optimization in logistics distribution based on Particle Swarm Optimization },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2019 },
volume = { 178 },
number = { 30 },
month = { Jul },
year = { 2019 },
issn = { 0975-8887 },
pages = { 23-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume178/number30/30728-2019919179/ },
doi = { 10.5120/ijca2019919179 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:51:51.465437+05:30
%A Appiah Martinson Yeboah
%A Xiong Qiang
%T Route Optimization in logistics distribution based on Particle Swarm Optimization
%J International Journal of Computer Applications
%@ 0975-8887
%V 178
%N 30
%P 23-27
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Vehicle Routing Problem (VRP) addresses a problem which identifies routes scheduled for vehicles moving from a distribution center to serve specific customers and returns to the distribution center. Notwithstanding, cost associated with transportation of business have drawn much attention in the past few years owing to the recent rise in fuel prices, therefore this paper study’s the problem of routing in cold chain logistics distribution with the goal of minimizing the total transportation cost. In this paper a single objective model is formulated and then solved by the Particle Swarm Optimization algorithm. A computational experiment is carried by the proposed model to obtain optimal distance and imputed in to the cost function to obtain the optimal cost. We found that an increase in population size and the number of iterations gives better minimization results.

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Index Terms

Computer Science
Information Sciences

Keywords

Particle Swarm Algorithm Vehicle Routing Problem Capacitated Vehicle Routing Problem

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