The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2018.091138
PDF

A Hybrid Genetic Algorithm with Tabu Search for Optimization of the Traveling Thief Problem

Author 1: Saad T Alharbi

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 11, 2018.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Until now, several approaches such as evolutionary computing and heuristic methods have been presented to optimize the traveling thief problem (TTP). However, most of these approaches consider the TTP components independently, usually considering the traveling salesman problem (TSP) and then tackling the knapsack problem (KP), despite their interdependent nature. In this paper, we investigate the use of a hybrid genetic algorithm (GA) and tabu search (TS) for the TTP. Therefore, a novel hybrid genetic approach called GATS is proposed and compared with the state-of-the-art approaches. The key aspect of GATS is that TTP solutions are considered by firmly taking into account the interdependent nature of the TTP subcomponents, where all its operators are simultaneously implemented on TSP and KP solutions. A comprehensive set of TTP benchmark datasets was adopted to investigate the effectiveness of GATS. We selected 540 instances for our investigation, which comprised five different groups of cities (51, 52, 76, 100 and 150 cities) and different groupings of items, from 50 to 745 items. All types of knapsack (uncorrelated, uncorrelated with similar weights and bonded strongly correlated) with all different knapsack capacities were also taken into consideration. Different initialization methods were empirically investigated as well. The results of the computational experiments demonstrated that GATS is capable of surpassing the state-of-the-art results for various instances.

Keywords: Combinatorial; hybrid approaches; genetic algorithm; optimization; tabu search; TTP

Saad T Alharbi, “A Hybrid Genetic Algorithm with Tabu Search for Optimization of the Traveling Thief Problem” International Journal of Advanced Computer Science and Applications(IJACSA), 9(11), 2018. http://dx.doi.org/10.14569/IJACSA.2018.091138

@article{Alharbi2018,
title = {A Hybrid Genetic Algorithm with Tabu Search for Optimization of the Traveling Thief Problem},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.091138},
url = {http://dx.doi.org/10.14569/IJACSA.2018.091138},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {11},
author = {Saad T Alharbi}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org