Modified Search Solutions Based ABC with Mutation Algorithm for TSP

Authors

  • Umesh Gera Department of Computer Science, Shriram College of Engineering and Management, Gwalior, Madhya Pradesh, India
  • Aparajit Shrivastava Department of Computer Science, Shriram College of Engineering and Management, Gwalior, Madhya Pradesh, India

Keywords:

Artificial bee colony, ABC, mutation, ABCM, genetic algorithm, GA

Abstract

Swarm intelligence systems are basically made up of simple agents’ population, which are interacting locally with each other and with their surroundings. The artificial bee colony algorithm (ABC) is for aging behavior based optimization algorithm. In this paper, modified version of ABC algorithm, called as ABCM, is used. In this algorithm, two equations of original ABC algorithm are modified: First is the search equation of employed bee and second is the search equation of onlooker bee. These modified search equations greatly increase the exploration and exploitation of ABCM algorithm. Also in the ABCM algorithm, mutation operator is used after the employed bee phase of the ABCM algorithm. Proposed algorithm is implemented on travelling salesman problem and compared with the original ABC algorithm and ABC with SPV algorithm. Experimental results show that the proposed algorithm performance is better than the previous versions of ABC algorithm.

Cite this Article
Umesh Gera, Aparajit Shrivastava. Modified Search Solutions Based ABC with Mutation Algorithm for TSP. Journal of Artificial Intelligence Research & Advances. 2016; 3(2): 39–43p.

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Published

2016-09-06

Issue

Vol. 3 No. 2 (2016)

Section

Research Articles

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