Optimizing the Capacitated Vehicle Routing Problem at PQR Company: A Genetic Algorithm and Grey Wolf Optimizer Approach

Akhdan Arifuddin; Amalia Utamima; Faizal Mahananto; Retno Aulia Vinarti; Nita Fernanda

doi:10.1016/j.procs.2024.03.023

Optimizing the Capacitated Vehicle Routing Problem at PQR Company: A Genetic Algorithm and Grey Wolf Optimizer Approach

Akhdan Arifuddin, Amalia Utamima^*, Faizal Mahananto, Retno Aulia Vinarti, Nita Fernanda

^*Corresponding author for this work

Institut Teknologi Sepuluh Nopember

Research output: Contribution to journal › Conference article › peer-review

Abstract

Product distribution for companies in the industrial sector is an important issue as it is necessary to increase customer satisfaction and reduce costs. In this study, Nondominated-Sorting Genetic Algorithm II is used to solve Capacitated Vehicle Routing Problem in a case study dataset from the biggest fertilizer company in Indonesia. NSGA-II algorithm reduced the need for vehicles in product distribution with an advantage of 44.7%, while GWO algorithm yielded better results with an increase of time of 16.9%.

Original language	English
Pages (from-to)	420-427
Number of pages	8
Journal	Procedia Computer Science
Volume	234
DOIs	https://doi.org/10.1016/j.procs.2024.03.023
Publication status	Published - 2024
Event	7th Information Systems International Conference, ISICO 2023 - Washington, United States Duration: 26 Jul 2023 → 28 Jul 2023

Keywords

Capacitated Vehicle Routing Problem
Grey Wolf Optimizer
NSGA-II
Resource Efficiency

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.procs.2024.03.023

Cite this

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title = "Optimizing the Capacitated Vehicle Routing Problem at PQR Company: A Genetic Algorithm and Grey Wolf Optimizer Approach",

abstract = "Product distribution for companies in the industrial sector is an important issue as it is necessary to increase customer satisfaction and reduce costs. In this study, Nondominated-Sorting Genetic Algorithm II is used to solve Capacitated Vehicle Routing Problem in a case study dataset from the biggest fertilizer company in Indonesia. NSGA-II algorithm reduced the need for vehicles in product distribution with an advantage of 44.7%, while GWO algorithm yielded better results with an increase of time of 16.9%.",

keywords = "Capacitated Vehicle Routing Problem, Grey Wolf Optimizer, NSGA-II, Resource Efficiency",

author = "Akhdan Arifuddin and Amalia Utamima and Faizal Mahananto and Vinarti, {Retno Aulia} and Nita Fernanda",

note = "Publisher Copyright: {\textcopyright} 2023 The Authors. Published by Elsevier B.V.; 7th Information Systems International Conference, ISICO 2023 ; Conference date: 26-07-2023 Through 28-07-2023",

year = "2024",

doi = "10.1016/j.procs.2024.03.023",

language = "English",

volume = "234",

pages = "420--427",

journal = "Procedia Computer Science",

issn = "1877-0509",

publisher = "Elsevier BV",

}

TY - JOUR

T1 - Optimizing the Capacitated Vehicle Routing Problem at PQR Company

T2 - 7th Information Systems International Conference, ISICO 2023

AU - Arifuddin, Akhdan

AU - Utamima, Amalia

AU - Mahananto, Faizal

AU - Vinarti, Retno Aulia

AU - Fernanda, Nita

PY - 2024

Y1 - 2024

N2 - Product distribution for companies in the industrial sector is an important issue as it is necessary to increase customer satisfaction and reduce costs. In this study, Nondominated-Sorting Genetic Algorithm II is used to solve Capacitated Vehicle Routing Problem in a case study dataset from the biggest fertilizer company in Indonesia. NSGA-II algorithm reduced the need for vehicles in product distribution with an advantage of 44.7%, while GWO algorithm yielded better results with an increase of time of 16.9%.

AB - Product distribution for companies in the industrial sector is an important issue as it is necessary to increase customer satisfaction and reduce costs. In this study, Nondominated-Sorting Genetic Algorithm II is used to solve Capacitated Vehicle Routing Problem in a case study dataset from the biggest fertilizer company in Indonesia. NSGA-II algorithm reduced the need for vehicles in product distribution with an advantage of 44.7%, while GWO algorithm yielded better results with an increase of time of 16.9%.

KW - Capacitated Vehicle Routing Problem

KW - Grey Wolf Optimizer

KW - NSGA-II

KW - Resource Efficiency

UR - http://www.scopus.com/inward/record.url?scp=85193200479&partnerID=8YFLogxK

U2 - 10.1016/j.procs.2024.03.023

DO - 10.1016/j.procs.2024.03.023

M3 - Conference article

AN - SCOPUS:85193200479

SN - 1877-0509

VL - 234

SP - 420

EP - 427

JO - Procedia Computer Science

JF - Procedia Computer Science

Y2 - 26 July 2023 through 28 July 2023

ER -

Optimizing the Capacitated Vehicle Routing Problem at PQR Company: A Genetic Algorithm and Grey Wolf Optimizer Approach

Abstract

Keywords

UN SDGs

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