Study of Some Recent Crossovers Effects on Speed and Accuracy of Genetic\n Algorithm, Using Symmetric Travelling Salesman Problem

2015/04/10 by Hassan Ismkhan, Ismkhan, Hassan, Kamran Zamanifar +1
Computer Science · Decision Sciences · Engineering · #FOS: Computer and information sciences #Metaheuristic Optimization Algorithms Research #Neural and Evolutionary Computing (cs.NE) #Scheduling and Timetabling Solutions #Vehicle Routing Optimization Methods

paper · pdf · doi:10.48550/arxiv.1504.02590

openalex publication_date 2015/04/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

The Travelling Salesman Problem (TSP) is one of the most famous optimization\nproblems. The Genetic Algorithm (GA) is one of metaheuristics that have been\napplied to TSP. The Crossover and mutation operators are two important elements\nof GA. There are many TSP solver crossover operators. In this paper, we state\nimplementation of some recent TSP solver crossovers at first and then we use\neach of them in GA to solve some Symmetric TSP (STSP) instances and finally\ncompare their effects on speed and accuracy of presented GA.\n

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