Volume 36, Issue 2 (IJIEPR 2025)                   IJIEPR 2025, 36(2): 170-184 | Back to browse issues page

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Aliyari Boroujeni A, Khadivar A. Solving the Traveling Salesman Problem Using a Modified Teaching-Learning Based Optimization Algorithm. IJIEPR 2025; 36 (2) :170-184
URL: http://ijiepr.iust.ac.ir/article-1-2111-en.html
Solving the Traveling Salesman Problem Using a Modified Teaching-Learning Based Optimization Algorithm
Ahmad Aliyari Boroujeni1 , Ameneh Khadivar2
1- Department of management, Faculty of Social Sciences and Economics Alzahra University, Tehran, Iran
2- Department of management, Faculty of Social Sciences and Economics Alzahra University, Tehran, Iran , a.khadivar@alzahra.ac.ir
Abstract:   (422 Views)
The Traveling Salesman Problem (TSP) is a well-known problem in optimization and graph theory, where finding the optimal solution has always been of significant interest. Optimal solutions to TSP can help reduce costs and increase efficiency across various fields. Heuristic algorithms are often employed to solve TSP, as they are more efficient than exact methods due to the complexity and large search space of the problem. In this study, meta-heuristic algorithms such as the Genetic Algorithm and the Teaching-Learning Based Optimization (TLBO) algorithm are used to solve the TSP. Additionally, a discrete mutation phase is introduced to the TLBO algorithm to enhance its performance in solving the TSP. The results indicate that, in testing two specific models of the TSP, the modified TLBO algorithm outperforms both the Genetic Algorithm and the standard TLBO algorithm in terms of convergence to the optimal solution and response time.
Keywords: Traveling Salesman problem, Modified Teaching-Learning Based, Optimization, Meta-heuristic algorithms, Graph theory
Full-Text [PDF 1023 kb]   (36 Downloads)    
Type of Study: Research | Subject: Optimization Techniques
Received: 2024/09/9 | Accepted: 2025/04/15 | Published: 2025/06/30
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