A multi-population harmony search algorithm for the dynamic travelling salesman problem with traffic factors

Mohanad Muayad John Jurjee, Hafiz Mohd Sarim, Noora Hani Abdulmajeed Al-Dabbagh, Erna Budhiarti Nababan

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Recently, there has been a growing attention to employ evolutionary algorithms (EAs) in addressing dynamic optimisation problems (DOPs) due to its significance in real world applications. The most notable challenge when solving DOPs is that the objective should not only attempt to seek the global optimum by an efficient way, but be able to keep track the optimal solution during the environmental changes. Thus, several mechanisms have been developed for EAs in order to improve the search performance of the algorithm in accommodating the dynamic changes such as by increasing the diversity of the population. Among these strategies, the multi-population mechanism has been found beneficial for EAs for DOPs. Dynamic travelling salesman problems (DTSPs) are categorised under DOPs. In the Travelling Salesman Problem (TSP), a salesman wants to distribute items sold in different cities starting from his home city and returning after he visited all the cities to his starting city again by optimising his time and tour efficiently. However, in the DTSPs, it is more challenging to consider the traffic delays that may affect the route of the salesman and change the time planned beforehand. Therefore, the salesman will optimise his time again and find a new alternative route to avoid long traffic delays. The presented work aims to build upon the state of the art research methodologies for the DTSPs with traffic factors, where in order to cope with the dynamic behaviour, a multi-population approach is applied to harmony search algorithm that mimics the musical process of trying to find a state of harmony. Moreover, a multiple pitch adjustment rate (PAR) strategy is proposed since PAR assumed to be the moving rate from one city to the nearest city in the TSP. The performance of the proposed multi-population HS algorithm is verified on two variations of DTSPs with traffic factors, i.e., random and cyclic traffic delays. Based on different DTSP test cases, the experimental results show that the proposed approach is able to obtain competitive results when compared to the best-known results in the scientific literature.

Original languageEnglish
Pages (from-to)265-284
Number of pages20
JournalJournal of Theoretical and Applied Information Technology
Volume95
Issue number2
Publication statusPublished - 31 Jan 2017

Fingerprint

Harmony Search
Traveling salesman problem
Travelling salesman problems
Search Algorithm
Traffic
Dynamic Optimization Problems
Evolutionary Algorithms
Evolutionary algorithms
Adjustment
Global Optimum
Real-world Applications
Dynamic Behavior
Optimal Solution
Optimise
Methodology
Alternatives
Experimental Results

Keywords

  • Diversity
  • Dynamic Optimisation
  • Harmony Search
  • Multi-Population Approach
  • Travelling Salesman Problem (TSP)

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

A multi-population harmony search algorithm for the dynamic travelling salesman problem with traffic factors. / Jurjee, Mohanad Muayad John; Mohd Sarim, Hafiz; Al-Dabbagh, Noora Hani Abdulmajeed; Nababan, Erna Budhiarti.

In: Journal of Theoretical and Applied Information Technology, Vol. 95, No. 2, 31.01.2017, p. 265-284.

Research output: Contribution to journalArticle

Jurjee, Mohanad Muayad John ; Mohd Sarim, Hafiz ; Al-Dabbagh, Noora Hani Abdulmajeed ; Nababan, Erna Budhiarti. / A multi-population harmony search algorithm for the dynamic travelling salesman problem with traffic factors. In: Journal of Theoretical and Applied Information Technology. 2017 ; Vol. 95, No. 2. pp. 265-284.
@article{63fbe4d61af24c6590067b2508697439,
title = "A multi-population harmony search algorithm for the dynamic travelling salesman problem with traffic factors",
abstract = "Recently, there has been a growing attention to employ evolutionary algorithms (EAs) in addressing dynamic optimisation problems (DOPs) due to its significance in real world applications. The most notable challenge when solving DOPs is that the objective should not only attempt to seek the global optimum by an efficient way, but be able to keep track the optimal solution during the environmental changes. Thus, several mechanisms have been developed for EAs in order to improve the search performance of the algorithm in accommodating the dynamic changes such as by increasing the diversity of the population. Among these strategies, the multi-population mechanism has been found beneficial for EAs for DOPs. Dynamic travelling salesman problems (DTSPs) are categorised under DOPs. In the Travelling Salesman Problem (TSP), a salesman wants to distribute items sold in different cities starting from his home city and returning after he visited all the cities to his starting city again by optimising his time and tour efficiently. However, in the DTSPs, it is more challenging to consider the traffic delays that may affect the route of the salesman and change the time planned beforehand. Therefore, the salesman will optimise his time again and find a new alternative route to avoid long traffic delays. The presented work aims to build upon the state of the art research methodologies for the DTSPs with traffic factors, where in order to cope with the dynamic behaviour, a multi-population approach is applied to harmony search algorithm that mimics the musical process of trying to find a state of harmony. Moreover, a multiple pitch adjustment rate (PAR) strategy is proposed since PAR assumed to be the moving rate from one city to the nearest city in the TSP. The performance of the proposed multi-population HS algorithm is verified on two variations of DTSPs with traffic factors, i.e., random and cyclic traffic delays. Based on different DTSP test cases, the experimental results show that the proposed approach is able to obtain competitive results when compared to the best-known results in the scientific literature.",
keywords = "Diversity, Dynamic Optimisation, Harmony Search, Multi-Population Approach, Travelling Salesman Problem (TSP)",
author = "Jurjee, {Mohanad Muayad John} and {Mohd Sarim}, Hafiz and Al-Dabbagh, {Noora Hani Abdulmajeed} and Nababan, {Erna Budhiarti}",
year = "2017",
month = "1",
day = "31",
language = "English",
volume = "95",
pages = "265--284",
journal = "Journal of Theoretical and Applied Information Technology",
issn = "1992-8645",
publisher = "Asian Research Publishing Network (ARPN)",
number = "2",

}

TY - JOUR

T1 - A multi-population harmony search algorithm for the dynamic travelling salesman problem with traffic factors

AU - Jurjee, Mohanad Muayad John

AU - Mohd Sarim, Hafiz

AU - Al-Dabbagh, Noora Hani Abdulmajeed

AU - Nababan, Erna Budhiarti

PY - 2017/1/31

Y1 - 2017/1/31

N2 - Recently, there has been a growing attention to employ evolutionary algorithms (EAs) in addressing dynamic optimisation problems (DOPs) due to its significance in real world applications. The most notable challenge when solving DOPs is that the objective should not only attempt to seek the global optimum by an efficient way, but be able to keep track the optimal solution during the environmental changes. Thus, several mechanisms have been developed for EAs in order to improve the search performance of the algorithm in accommodating the dynamic changes such as by increasing the diversity of the population. Among these strategies, the multi-population mechanism has been found beneficial for EAs for DOPs. Dynamic travelling salesman problems (DTSPs) are categorised under DOPs. In the Travelling Salesman Problem (TSP), a salesman wants to distribute items sold in different cities starting from his home city and returning after he visited all the cities to his starting city again by optimising his time and tour efficiently. However, in the DTSPs, it is more challenging to consider the traffic delays that may affect the route of the salesman and change the time planned beforehand. Therefore, the salesman will optimise his time again and find a new alternative route to avoid long traffic delays. The presented work aims to build upon the state of the art research methodologies for the DTSPs with traffic factors, where in order to cope with the dynamic behaviour, a multi-population approach is applied to harmony search algorithm that mimics the musical process of trying to find a state of harmony. Moreover, a multiple pitch adjustment rate (PAR) strategy is proposed since PAR assumed to be the moving rate from one city to the nearest city in the TSP. The performance of the proposed multi-population HS algorithm is verified on two variations of DTSPs with traffic factors, i.e., random and cyclic traffic delays. Based on different DTSP test cases, the experimental results show that the proposed approach is able to obtain competitive results when compared to the best-known results in the scientific literature.

AB - Recently, there has been a growing attention to employ evolutionary algorithms (EAs) in addressing dynamic optimisation problems (DOPs) due to its significance in real world applications. The most notable challenge when solving DOPs is that the objective should not only attempt to seek the global optimum by an efficient way, but be able to keep track the optimal solution during the environmental changes. Thus, several mechanisms have been developed for EAs in order to improve the search performance of the algorithm in accommodating the dynamic changes such as by increasing the diversity of the population. Among these strategies, the multi-population mechanism has been found beneficial for EAs for DOPs. Dynamic travelling salesman problems (DTSPs) are categorised under DOPs. In the Travelling Salesman Problem (TSP), a salesman wants to distribute items sold in different cities starting from his home city and returning after he visited all the cities to his starting city again by optimising his time and tour efficiently. However, in the DTSPs, it is more challenging to consider the traffic delays that may affect the route of the salesman and change the time planned beforehand. Therefore, the salesman will optimise his time again and find a new alternative route to avoid long traffic delays. The presented work aims to build upon the state of the art research methodologies for the DTSPs with traffic factors, where in order to cope with the dynamic behaviour, a multi-population approach is applied to harmony search algorithm that mimics the musical process of trying to find a state of harmony. Moreover, a multiple pitch adjustment rate (PAR) strategy is proposed since PAR assumed to be the moving rate from one city to the nearest city in the TSP. The performance of the proposed multi-population HS algorithm is verified on two variations of DTSPs with traffic factors, i.e., random and cyclic traffic delays. Based on different DTSP test cases, the experimental results show that the proposed approach is able to obtain competitive results when compared to the best-known results in the scientific literature.

KW - Diversity

KW - Dynamic Optimisation

KW - Harmony Search

KW - Multi-Population Approach

KW - Travelling Salesman Problem (TSP)

UR - http://www.scopus.com/inward/record.url?scp=85011711358&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85011711358&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:85011711358

VL - 95

SP - 265

EP - 284

JO - Journal of Theoretical and Applied Information Technology

JF - Journal of Theoretical and Applied Information Technology

SN - 1992-8645

IS - 2

ER -