Abstract—This paper presents the meta-heuristic method of ant colony optimization (ACO) to find optimal paths on terrain map images. The procedure simulates decision-making process of ant colonies as they forage for food. Modifications have been made to the ACO algorithm to solve the optimal path finding problem by optimizing multiple constraints. The number of constraints considered here is two. However, it can effectively be used for more than two constraints.
Index Terms—Ant Algorithms, Meta-heuristic, Multiple Objective Optimization
Vinay Rishiwal is with the MJP Rohilkhand University, Bareilly, UP, India. (Phone: 915812520310; fax: 915812520310; (e-mail: vrishiwal@mjpru.ac.in).
Mano Yadav is with ITS Engineering College, Greater Noida, UP, India. (E-mail: mano425@iiita.ac.in).
Dr. K. V. Arya is with the ABV- Indian Institute of Information Technology, Gwalior, India. He is working as an Associate Prof. in the Department of Information Technology. (E-mail: kvarya@gmail.com)
Cite: Vinay Rishiwal, Mano Yadav, K. V. Arya, "Finding Optimal Paths on Terrain Maps using Ant Colony Algorithm," International Journal of Computer Theory and Engineering vol. 2, no. 3, pp. 416-419, 2010.
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