MGA-TSP: modernised genetic algorithm for the travelling salesman problem

Al-Khatib, Ra’ed M.; Al-Betar, Mohammed Azmi; Awadallah, Mohammed A.; Nahar, Khalid M.O.; Shquier, Mohammed M. Abu; Manasrah, Ahmad M.; Doumi, Ahmad Bany

doi:10.1504/ijris.2019.102541

Cited by 3 publications

(1 citation statement)

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“…The search space of N cities in the TSP case has (N-1)! potential solutions [29]. That is to say, there will be 40320 different paths to get from one city to another.…”

Section: Resultsmentioning

confidence: 99%

Analysis study of the bee algorithms as a mechanism for solving combinatorial problems

Shabat

Raheem

2023

IJEECS

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Combinatorial optimization problems are problems that have a large number of discrete solutions and a cost function for evaluating those solutions in comparison to one another. With the vital need of solving the combinatorial problem, several research efforts have been concentrated on the biological entities behaviors to utilize such behaviors in population-based metaheuristic. This paper presents bee colony algorithms which is one of the sophisticated biological nature life. A brief detail of the nature of bee life has been presented with further classification of its behaviors. Furthermore, an illustration of the algorithms that have been derived from bee colony which are bee colony optimization, and artificial bee colony. Finally, a comparative analysis has been conducted between these algorithms according to the results of the traveling salesman problem solution. Where the bee colony optimization (BCO) rendered the best performance in terms of computing time and results.

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“…The search space of N cities in the TSP case has (N-1)! potential solutions [29]. That is to say, there will be 40320 different paths to get from one city to another.…”

Section: Resultsmentioning

confidence: 99%