Pepper, J.W., Golden, B.L. and Wasil, E.A. (2002) Solving the Traveling Salesman Problem with Annealing-Based Heuristics: A Computational Study. IEEE Transactions on System, Man, Cybernetics, Part A: Systems and Humans, 32, 72-77.
https://doi.org/10.1109/3468.995530

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.