Volume 6, Issue 4 (10-2016)                   IJOCE 2016, 6(4): 469-492 | Back to browse issues page

XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Kaveh A, Zolghadr A. A NOVEL META-HEURISTIC ALGORITHM: TUG OF WAR OPTIMIZATION. IJOCE 2016; 6 (4) :469-492
URL: http://ijoce.iust.ac.ir/article-1-265-en.html
Abstract:   (24624 Views)

This paper presents a novel population-based meta-heuristic algorithm inspired by the game of tug of war. Utilizing a sport metaphor the algorithm, denoted as Tug of War Optimization (TWO), considers each candidate solution as a team participating in a series of rope pulling competitions.  The  teams  exert  pulling  forces  on  each  other  based  on  the  quality  of  the solutions  they  represent.  The  competing  teams  move  to  their  new  positions  according  to Newtonian laws of mechanics. Unlike many other meta-heuristic methods, the algorithm is formulated  in  such  a  way  that  considers  the  qualities  of  both  of  the  interacting  solutions. TWO  is  applicable  to  global  optimization  of  discontinuous,  multimodal,  non-smooth,  and non-convex functions. Viability of the proposed method is examined using some benchmark mathematical functions and engineering design problems. The numerical results indicate the efficiency of the proposed algorithm compared to some other methods available in literature.

Full-Text [PDF 845 kb]   (8635 Downloads)    
Type of Study: Research | Subject: Optimal design
Received: 2016/03/2 | Accepted: 2016/03/2 | Published: 2016/03/2

Add your comments about this article : Your username or Email:
CAPTCHA

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Iran University of Science & Technology

Designed & Developed by : Yektaweb