Bi-objective covering salesman problem with uncertainty

Humanitarian relief transportation and mass fatality management activities are the most strenuous tasks after a natural or artificial disaster. A feasible and realistic transport model is essential for accomplishing the tasks in a planned way. Covering Salesman Problem (CSP) is a variant of Travelin...

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Veröffentlicht in:Journal of Decision Analytics and Intelligent Computing Jg. 3; H. 1; S. 122 - 138
1. Verfasser: Tripathy, Siba Prasada
Format: Journal Article
Sprache:Englisch
Veröffentlicht: 15.08.2023
ISSN:2787-2572, 2787-2572
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Beschreibung
Zusammenfassung:Humanitarian relief transportation and mass fatality management activities are the most strenuous tasks after a natural or artificial disaster. A feasible and realistic transport model is essential for accomplishing the tasks in a planned way. Covering Salesman Problem (CSP) is a variant of Traveling Salesman Problem (TSP) which has been used in many application areas, including disaster management. In this paper, we consider a bi-objective CSP in an uncertain environment where Interval Type 2 fuzzy numbers represent the costs of the edges. A new local search technique is introduced in the memetic algorithm, which has been used to solve the problem. A computational experiment on a set of instances indicates the effectiveness of the introduced local search technique along with the proposed methodology.
ISSN:2787-2572
2787-2572
DOI:10.31181/jdaic10015082023t