2009Unpublished venueRequires access

Genetic algorithm for Traveling Salesman Problem: Using modified Partially-Mapped Crossover operator

Vijendra Singh, S. Choudhary

Open publisher page 13 citations

Abstract

This paper addresses an attempt to evolve genetic algorithm by a particular modified partially mapped crossover method to make it able to solve the Traveling Salesman Problem. Which is type of NP-hard combinatorial optimization problems. The main objective is to look a better GA such that solves TSP with shortest tour. First we solve the TSP by using PMX (Goldberg and Lingle, 1985) and then a modified PMX to evolve a GA.

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What this paper is about

This paper addresses an attempt to evolve genetic algorithm by a particular modified partially mapped crossover method to make it able to solve the Traveling Salesman Problem. Which is type of NP-hard combinatorial optimization problems. The main objective is to look a better GA such that solves TSP with shortest tour. First we solve the TSP by using PMX (Goldberg and Lingle, 1985) and then a modified PMX to evolve a GA.

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OpenAlex reports 13 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper addresses an attempt to evolve genetic algorithm by a particular modified partially mapped crossover method to make it able to solve the Traveling Salesman Problem. Which is type of NP-hard combinatorial optimization problems. The main objective is to look a better GA such that solves TSP with shortest tour. First we solve the TSP by using PMX (Goldberg and Lingle, 1985) and then a modified PMX to evolve a GA.

Key concepts: Travelling salesman problem, Crossover, Genetic algorithm, Operator (biology), Mathematical optimization, Computer science, Algorithm, Combinatorial optimization

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