Memetic Algorithm based on Improved Inver-over operator and Lin-Kernighan local search for the Euclidean traveling salesman problem

Authors:
Yu-Ting Wang;Jun-Qing Li;Kai-Zhou Gao;Quan-Ke Pan
Affiliations:
College of Computer Science, Liaocheng University, PR China;College of Computer Science, Liaocheng University, PR China;College of Computer Science, Liaocheng University, PR China;State Key Laboratory of Synthetical Automation for Process Industries (Northeastern University), Shenyang, 110819, PR China
Venue:
Computers & Mathematics with Applications
Year:
2011

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Abstract

In this study, an Improved Inver-over operator is proposed to solve the Euclidean traveling salesman problem (TSP) problem. The Improved Inver-over operator is tested on 14 different TSP examples selected from TSPLIB. The application of the Improved Inver-over operator gives much more effective results regarding to the best and average error values than the Basic Inver-over operator. Then an effective Memetic Algorithm based on Improved Inver-over operator and Lin-Kernighan local search is implemented. To speed up the convergence capability of the presented algorithm, a restart technique is employed. We evaluate the proposed algorithm based on standard TSP test problems and show that the proposed algorithm performs better than other Memetic Algorithm in terms of solution quality and computational effort.