This is a preliminary version of a chapter that appeared in the book Local Search in Combinatorial Optimization, E. H. L. Aarts and J. K. Lenstra (eds.), John Wiley and Sons, London, 1997, pp. 215-310. The traveling salesman problem (TSP) has been an early proving ground for many approaches to combinatorial optimization, including clas- sical local optimization techniques as well as many of the more recent variants on local optimization, such as simulated annealing, tabu search, neural networks, and genetic algorithms. This chapter discusses how these various approaches have been adapted to the TSP and evaluates their relative success in this perhaps atypical domain from both a theoretical and an experimental point of view.
CITATION STYLE
Johnson, D. S., & McGeoch, L. A. (1997). The traveling salesman problem: A case study in local optimization. Local Search in Combinatorial Optimization, 215–310. Retrieved from http://142.103.6.5/~hutter/previous-earg/EmpAlgReadingGroup/TSP-JohMcg97.pdf
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