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Improvement of imperialist colony algorithm by employment of imperialist learning operator and implementing in travel salesman problem

Haleh, Hassan and Esmaeili Aliabadi, Danial (2015) Improvement of imperialist colony algorithm by employment of imperialist learning operator and implementing in travel salesman problem. Journal of Development & Evolution Management, 1394 (22). pp. 55-61.

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Official URL: http://www.jdem.ir/issue_27_33_Volume+1394%2C+Issue+22%2C+Autumn+2015%2C+Page+1-70.html

Abstract

This study tries to enhance imperialist colony algorithm (ICA) in the context of travel salesman problem (TSP). By adding new learning operator, imperialist learns from colonies that have suitable cost in which manner that improves the solution of problems. We believe that controlled learning improvement is better than uncontrolled one. The efficiency of new operator represented with the variety of instances from TSPLIB. We evaluate the approach on standard TSP test problems and show that it performs better, with respect to solution quality and computation time than ICA without new learning operator.

Item Type:Article
Uncontrolled Keywords:Travel Salesman Problem; Imperialist Colony Algorithm; Meta-Heuristic Algorithm; TSPLIB
Subjects:UNSPECIFIED
ID Code:31187
Deposited By:Danial Esmaeili Aliabadi
Deposited On:28 Apr 2017 14:54
Last Modified:28 Apr 2017 14:54

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