Comparative Excellence of Metaheuristic Algorithms in Stochastic TSP: Navigating Partial Visibility and Dynamic Edge Weights for Disaster Management Optimization

DOI

10.2991/978-94-6463-884-4_79How to use a DOI?

Keywords

Comparative analysis; Disaster Response; Metaheuristic Algorithm; NP-Hard Problem; Stochastic Traveling Salesman Problem

Abstract

Stochastic Traveling Salesman Problem (S-TSP) with Partial Visibility and Randomized Edge Weights is a critical challenge in disaster management where uncertainty and dynamic conditions hinder effective rescue operations. To address this, five optimization algorithms, Genetic Algorithm (GA), Ant Colony Optimization (ACO), Tabu Search (TS), Simulated Annealing (SA), and Nearest Neighbor Heuristic (NNH), implemented using Code::Blocks IDE and evaluated through simulation. Chrono measured execution time, providing insights into algorithmic efficiency under dynamic conditions. Memory utilization and computational overhead were analyzed using gperftools, which monitored evictions, interrupts, and byte usage. Valgrind’s Callgrind assessed instruction counts, offering a detailed evaluation of algorithm scalability and resource management. The comparative analysis highlighted NNH as the most effective algorithm, balancing computational efficiency with solution quality, making it highly suitable for real-time disaster response applications. The profiling tools reinforced these findings, identifying NNH’s capability to optimize memory and computation resources effectively. This research underscores the importance of using adaptable and efficient algorithms in disaster management, where rapid and accurate decision-making is crucial.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Eaoumoon Haque
AU  - Tahsinul Islam Nishat
AU  - Ragib Nadim
AU  - Noshin Saiyara Rahman
AU  - Md. Fahim Al Shihab
AU  - Md. Maruf Hossain Munna
AU  - Md. Faruk Abdullah Al Sohan
PY  - 2025
DA  - 2025/11/18
TI  - Comparative Excellence of Metaheuristic Algorithms in Stochastic TSP: Navigating Partial Visibility and Dynamic Edge Weights for Disaster Management Optimization
BT  - Proceedings of the 8th International Conference on Engineering Research, Innovation, and Education 2025 (ICERIE 2025)
PB  - Atlantis Press
SP  - 654
EP  - 662
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-884-4_79
DO  - 10.2991/978-94-6463-884-4_79
ID  - Haque2025
ER  -