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.2022.0130428
PDF

Stochastic Marine Predator Algorithm with Multiple Candidates

Author 1: Purba Daru Kusuma
Author 2: Ratna Astuti Nugrahaeni

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 4, 2022.

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

Abstract: This work proposes a metaheuristic algorithm that modifies the marine predator algorithm (MPA), namely, the stochastic marine predator algorithm with multiple candidates (SMPA-MC). The modification is conducted in several aspects. The proposed algorithm replaces the three fixed equal size iteration phases with linear probability. Unlike the original MPA, in this proposed algorithm, the selection between exploration and exploitation is conducted stochastically during iteration. In the beginning, the exploration-dominant strategy is implemented to increase the exploration probability. Then, during the iteration, the exploration probability decreases linearly. Meanwhile, the exploitation probability increases linearly. The second modification is in the prey’s guided movement. Different from the basic MPA, where the prey moves toward the elite with small step size, several candidates are generated with equal inter-candidate distance in this work. Then, the best candidate is chosen to replace the prey’s current location. The proposed algorithm is then implemented to solve theoretical mathematic functions and a real-world optimization problem in production planning. The simulation result shows that in the average fitness score parameter, the proposed algorithm is better than MPA, especially in solving multimodal functions. The simulation result also shows that the proposed algorithm creates 9%, 19%, and 30% better total gross profit than particle swarm optimization, marine predator algorithm, and Komodo mlipir algorithm, respectively.

Keywords: Metaheuristic; marine predator algorithm; stochastic system; production planning

Purba Daru Kusuma and Ratna Astuti Nugrahaeni, “Stochastic Marine Predator Algorithm with Multiple Candidates” International Journal of Advanced Computer Science and Applications(IJACSA), 13(4), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130428

@article{Kusuma2022,
title = {Stochastic Marine Predator Algorithm with Multiple Candidates},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130428},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130428},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {4},
author = {Purba Daru Kusuma and Ratna Astuti Nugrahaeni}
}



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