FINDING THE SHORTEST AND OPTIMAL PATH WITH METAHEURISTIC AND MADM METHODS

Authors

Narmin Ibrahim Hasanli, Azarbaijan State Oil and Industry University. Adress: Azadliq Avenue, 34, Baku city, Republic of Azerbaijan. E-mail: narmin.mammadova@gmail.com, Phone:+994-51-706-45-25.Follow

Abstract

The article had described a method for finding the shortest and most optimal path among cities. The data had been taken from the TSPLIB library, which had provided standard examples for the Traveling Salesman Problem. This approach had integrated the advantages of the meta-heuristic technique and the Multi Attribute Decision Making method to solve the problem effectively. In the first stage, the population based meta-heuristic method ACO (Ant Colony Optimization) had found optimal solutions in large search spaces. The use of pheromone trails, heuristic information and an iterative search process had given the opportunity to find the best or near-best solutions. It also had considered pheromone evaporation, which had helped the algorithm avoid getting stuck too early on a single solution and had maintained a balance between exploration and exploitation. Although ACO had produced several good solutions, it had been difficult to determine which one was the best. In such cases, the TOPSIS method, from Multi-Attribute Decision Making (MADM), has been used to compare these solutions based on multiple criteria and has ranked them according to their closeness to the ideal solution.

First Page

90

Last Page

95

References

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Recommended Citation

Hasanli, Narmin Ibrahim (2025) "FINDING THE SHORTEST AND OPTIMAL PATH WITH METAHEURISTIC AND MADM METHODS," Chemical Technology, Control and Management: Vol. 2025: Iss. 4, Article 11.
DOI: https://doi.org/10.59048/2181-1105.1705