The fitness landscape analysis of the ant colony system algorithm in solving a vehicle routing problem
In this article, we examine the effectiveness of the Ant Colony System (ACS) algorithm for a Vehicle Routing Problem (VRP). Fitness landscape analysis determines the complexity of the optimization search space. By analyzing the search space, we can conclude the complexity of the task, whether a given algorithm (its operators) is effective for a given type of task. When most researchers develop an algorithm, they test it on benchmark data. If this achieves the best result known so far for the bench-mark data (or are close to the big ones), the results will be published. However, in addition to existing tests, various analyzes can also be performed
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Hivatkozás
MLA: Agárdi, Anita, László Kovács, and Tamás Bányai. "The fitness landscape analysis of the ant colony system algorithm in solving a vehicle routing problem." ACADEMIC JOURNAL OF MANUFACTURING ENGI-NEERING 19.2 (2021).
APA: Agárdi, A., Kovács, L., & Bányai, T. (2021). The fitness landscape analysis of the ant colony system algorithm in solving a vehicle routing problem. ACADEMIC JOURNAL OF MANUFACTURING ENGI-NEERING, 19(2).
ISO690: AGÁRDI, Anita; KOVÁCS, László; BÁNYAI, Tamás. The fitness landscape analysis of the ant colony system algorithm in solving a vehicle routing problem. ACADEMIC JOURNAL OF MANUFACTURING ENGI-NEERING, 2021, 19.2.
BibTeX:
@article{agardi2021fitness,
title={The fitness landscape analysis of the ant colony system algorithm in solving a vehicle routing problem},
author={Ag{'a}rdi, Anita and Kov{'a}cs, L{'a}szl{'o} and B{'a}nyai, Tam{'a}s},
journal={ACADEMIC JOURNAL OF MANUFACTURING ENGI-NEERING},
volume={19},
number={2},
year={2021}
}