Modified Ant System Solving TSP Problem
Renu Jangra1, Ramesh Kait2
1Renu Jangra, Department of Computer Science and Applications, Kurukshetra University, Kurukshetra, India.
2Ramesh Kait, Department of Computer Science and Applications, Kurukshetra University, Kurukshetra, India.
Manuscript received on 08 June 2019 | Revised Manuscript received on 13 June 2019 | Manuscript Published on 08 July 2019 | PP: 328-331 | Volume-8 Issue-8S3 June 2019 | Retrieval Number: H10880688S319/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: ACO is applied on various combinatorial optimization problems. One among them is Travelling Salesman Problem. Generally, the fundamental ACO has the disadvantage of the entrapment in the local minimum and stagnation problem. In this paper, we proposed the algorithm named modified ant system (MAS) to resolve the above problems by modifying the pheromone update equation which results in better overall searching ability and also give better optimal solution earlier than AS. The comparison is done between basic ant system and modified ant system on different TSP problem instances. The proposed algorithm illustrates the less costlength of the tour taken by ants to discover the shortest pathway.
Keywords: Ant System (AS), Modified Ant System (MAS), Pheromone, Ant Colony Optimization (ACO).
Scope of the Article: Discrete Optimization