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Balas, E. and Toth, P. (1985) Branch and Bound Methods. In: Lawler, E.L., Lenstra, J.K., Rinnooy Kan, A.H.G. and Shmoys, D.B., Eds., The Traveling Salesman Problem: A Guided Tour of Combinatorial Optimization, John Wiley & Sons, New York, 80-147.

has been cited by the following article:

• 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.