On Enhanced Intelligent Water Drops Algorithm for Travelling Salesman Problem under Uncertain Paradigm

IF 1.1 Q3 TRANSPORTATION SCIENCE & TECHNOLOGY
Swapna Halder, H. Sharma, A. Biswas, O. Prentkovskis, S. Majumder, Paulius Skačkauskas
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引用次数: 1

Abstract

Abstract Travelling salesman problem (TSP) is a well known combinatorial optimization problem which has drawn colossal attention due to its eclectic range of applications. In this article, we have proposed two modified versions of intelligent water drops (IWD) algorithm. The first one is the enhanced IWD (e-IWD) algorithm to solve single objective TSP. In the second modification, e-IWD algorithm has been extended to enhanced multi-objective IWD(e-MIWD) algorithm for solving multi-objective TSP. In order to achieve a better exploration capability in both of the proposed algorithms, the soil and velocity parameters of a randomly selected water drop are updated after every iteration of the algorithm when it traverses all the intermediate vertices for a tour. The proposed algorithms have been compared with some other existing similar algorithms on different benchmark instances of TSPs. Furthermore, we have addressed the TSP for both single and multiple objectives under uncertain environment.
不确定范式下旅行商问题的增强智能水滴算法
旅行商问题(TSP)是一个著名的组合优化问题,由于其广泛的应用范围而引起了广泛的关注。本文提出了两种改进版本的智能水滴(IWD)算法。第一个是求解单目标TSP的增强型IWD (e-IWD)算法。在第二次修正中,e-IWD算法扩展为求解多目标TSP的增强型多目标IWD(e-MIWD)算法。为了获得更好的探测能力,算法在遍历所有中间点时,每次迭代后都会更新随机选择的水滴的土壤和速度参数。在不同的tsp基准实例上,将所提出的算法与现有的一些类似算法进行了比较。此外,我们还讨论了不确定环境下单目标和多目标的TSP问题。
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来源期刊
Transport and Telecommunication Journal
Transport and Telecommunication Journal TRANSPORTATION SCIENCE & TECHNOLOGY-
CiteScore
3.00
自引率
0.00%
发文量
21
审稿时长
35 weeks
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