Recombination Operators in Permutation-Based Evolutionary Algorithms for the Travelling Salesman Problem

Abstract

The Travelling Salesman Problem (TSP) is one of the most widely studied optimization problems due to its many applications in domains such as logistics, planning, routing, and scheduling. Approximation algorithms to address this NP-hard problem include genetic algorithms, ant colony systems, and simulated annealing. This chapter concentrates on the evolutionary approaches to TSP based on permutation encoded individuals. A comparative analysis of several recombination operators is presented based on computational experiments for TSP instances and a generalized version of TSP. Numerical results emphasize a good performance of two proposed crossover schemes: best-worst recombination and best order recombination which take into account information from the global best and/or worst individuals besides the genetic material from parents.