Non-dominated Sorting Tournament Genetic Algorithm for Multi-Objective Travelling Salesman Problem

P. Myszkowski, Maciej Laszczyk, Kamil Dziadek
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引用次数: 3

Abstract

A Travelling Salesman Problem (TSP) is an NP-hard combinatorial problem that is very important for many real-world applications. In this paper, it is shown, that proposed approach solves multi-objective TSP (mTSP) more effectively than other investigated methods, i.e., Non-dominated Sorting Genetic Algorithm II (NSGA-II). The proposed methods use rank and crowding distance (well-known from NSGA-II), combining those mechanisms in a novel, unique way: competing and co-evolving in the evolution process. The proposed modifications are investigated and verified by the benchmark mTSP instances, and results are compared to other methods.
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多目标旅行商问题的非支配排序竞赛遗传算法
旅行商问题(TSP)是一个NP-hard组合问题,在许多实际应用中非常重要。本文的研究表明,该方法比非支配排序遗传算法(NSGA-II)更有效地求解多目标TSP (mTSP)问题。所提出的方法使用秩和拥挤距离(众所周知的NSGA-II),以一种新颖独特的方式结合这些机制:在进化过程中竞争和共同进化。通过mTSP基准实例对所提出的改进进行了研究和验证,并将结果与其他方法进行了比较。
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