scholarly journals An application of fruit fly optimization algorithm for traveling salesman problem

2017 ◽  
Vol 111 ◽  
pp. 58-63 ◽  
Author(s):  
Hazim Iscan ◽  
Mesut Gunduz
Keyword(s):  
Traveling Salesman Problem ◽  
Optimization Algorithm ◽  
Fruit Fly ◽  
Traveling Salesman ◽  
Fruit Fly Optimization Algorithm ◽  
Fruit Fly Optimization

scholarly journals Comparative Solutions of Exact and Approximate Methods for Traveling Salesman Problem

Lámpsakos ◽  
2021 ◽  
pp. 3804
Author(s):  
Agung Chandra ◽  
Christine Natalia ◽  
Aulia Naro
Keyword(s):  
Approximate Method ◽  
Traveling Salesman Problem ◽  
Fruit Fly ◽  
Optimization Methods ◽  
Traveling Salesman ◽  
Exact Method ◽  
Fruit Fly Optimization Algorithm ◽  
Approximate Methods ◽  
Fruit Fly Optimization ◽  
Exact And Approximate Methods

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.

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