JOURNAL ARTICLE

Solving Traveling Salesman Problem by Using Combinatorial Artificial Bee Colony Algorithms

Derviş KaraboğaBeyza Görkemli

Year: 2019 Journal:   International Journal of Artificial Intelligence Tools Vol: 28 (01)Pages: 1950004-1950004   Publisher: World Scientific

Abstract

Artificial bee colony (ABC) is a quite popular optimization approach that has been used in many fields, with its not only standard form but also improved versions. In this paper, new versions of ABC algorithm to solve TSP are introduced and described in detail. One of these is the combinatorial version of standard ABC, called combinatorial ABC (CABC) algorithm. The other one is an improved version of CABC algorithm, called quick CABC (qCABC) algorithm. In order to see the efficiency of the new versions, 15 different TSP benchmarks are considered and the results generated are compared with different well-known optimization methods. The simulation results show that, both CABC and qCABC algorithms demonstrate good performance for TSP and also the new definition in quick ABC (qABC) improves the convergence performance of CABC on TSP.

Keywords:
Travelling salesman problem Computer science Artificial bee colony algorithm Convergence (economics) Combinatorial optimization Algorithm Mathematical optimization Ant colony optimization algorithms Artificial intelligence Mathematics

Metrics

63
Cited By
6.61
FWCI (Field Weighted Citation Impact)
26
Refs
0.97
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Metaheuristic Optimization Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence
Scheduling and Timetabling Solutions
Social Sciences →  Decision Sciences →  Management Science and Operations Research
Vehicle Routing Optimization Methods
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering

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