TITLE:
A Rule Based Evolutionary Optimization Approach for the Traveling Salesman Problem
AUTHORS:
Wissam M. Alobaidi, David J. Webb, Eric Sandgren
KEYWORDS:
Traveling Salesman, Evolutionary Optimization, Rule Based Search, Heuristic Optimization, Hybrid Genetic Algorithm
JOURNAL NAME:
Intelligent Information Management,
Vol.9 No.4,
July
14,
2017
ABSTRACT: The traveling salesman problem has long been regarded as a challenging application for existing optimization methods as well as a benchmark application for the development of new optimization methods. As with many existing algorithms, a traditional genetic algorithm will have limited success with this problem class, particularly as the problem size increases. A rule based genetic algorithm is proposed and demonstrated on sets of traveling salesman problems of increasing size. The solution character as well as the solution efficiency is compared against a simulated annealing technique as well as a standard genetic algorithm. The rule based genetic algorithm is shown to provide superior performance for all problem sizes considered. Furthermore, a post optimal analysis provides insight into which rules were successfully applied during the solution process which allows for rule modification to further enhance performance.