Comparative Solutions of Exact and Approximate Methods for Traveling Salesman Problem

IF 0.1 Q4 ENGINEERING, MULTIDISCIPLINARY
A. Chandra, C. Natalia, Aulia Naro
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引用次数: 0

Abstract

There are two major optimization methods: Exact and Approximate methods. A well known exact method, Branch and Bound algorithm (B&B) and approximate methods, Elimination-based Fruit Fly Optimization Algorithm (EFOA) and Artificial Atom Algorithm (A3) are used for solving the Traveling Salesman Problem (TSP). For 56 destinations, the results of total distance, processing time, and the deviation between exact and approximate method will be compared where the distance between two destinations is a Euclidean distance and this study shows that the distance of B&B is 270 , EFOA is 270 and A3 is 288.38 which deviates 6.81%. For time processing aspect, B&B needs 12.5 days to process, EFOA needs 36.59 seconds, A3 needs 35.34 seconds. But for 29 destinations, exact method is more powerful than approximate method.
旅行商问题精确与近似方法的比较解
有两种主要的优化方法:精确法和近似法。求解旅行商问题(TSP)的方法主要有精确方法、分支定界算法(B&B)和近似方法、基于消除的果蝇优化算法(EFOA)和人工原子算法(A3)。对于56个目的地,将比较总距离、处理时间以及精确法与近似法的偏差结果,其中两个目的地之间的距离为欧几里得距离,本研究表明B&B的距离为270,EFOA为270,A3为288.38,偏差为6.81%。在时间处理方面,B&B需要12.5天处理,EFOA需要36.59秒,A3需要35.34秒。但对于29个目的地,精确方法比近似方法更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Revista Digital Lampsakos
Revista Digital Lampsakos ENGINEERING, MULTIDISCIPLINARY-
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审稿时长
12 weeks
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