Fennec Adaptive Cooling Algorithm (FACA): A Novel Nature-Inspired Metaheuristic Drawn From Algerian Wildlife

Conference paper

Safia El-Imane Bousalmi, Khalid Hachemi
Proceedings of the International Conference on Industrial Maintenance and Production Engineering (ICIMPE 2024), University of Oran 2 Mohamed Ben Ahmed, Oran, Algeria, 2024

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APA Click to copy
Bousalmi, S. E.-I., & Hachemi, K. (2024). Fennec Adaptive Cooling Algorithm (FACA): A Novel Nature-Inspired Metaheuristic Drawn From Algerian Wildlife. In Proceedings of the International Conference on Industrial Maintenance and Production Engineering (ICIMPE 2024). Oran, Algeria: University of Oran 2 Mohamed Ben Ahmed.

Chicago/Turabian Click to copy
Bousalmi, Safia El-Imane, and Khalid Hachemi. “Fennec Adaptive Cooling Algorithm (FACA): A Novel Nature-Inspired Metaheuristic Drawn From Algerian Wildlife.” In Proceedings of the International Conference on Industrial Maintenance and Production Engineering (ICIMPE 2024). Oran, Algeria: University of Oran 2 Mohamed Ben Ahmed, 2024.

MLA Click to copy
Bousalmi, Safia El-Imane, and Khalid Hachemi. “Fennec Adaptive Cooling Algorithm (FACA): A Novel Nature-Inspired Metaheuristic Drawn From Algerian Wildlife.” Proceedings of the International Conference on Industrial Maintenance and Production Engineering (ICIMPE 2024), University of Oran 2 Mohamed Ben Ahmed, 2024.

BibTeX Click to copy

@inproceedings{bousalmi2024a,
  title = {Fennec Adaptive Cooling Algorithm (FACA): A Novel Nature-Inspired Metaheuristic Drawn From Algerian Wildlife},
  year = {2024},
  address = {Oran, Algeria},
  organization = {University of Oran 2 Mohamed Ben Ahmed},
  author = {Bousalmi, Safia El-Imane and Hachemi, Khalid},
  booktitle = {Proceedings of the International Conference on Industrial Maintenance and Production Engineering (ICIMPE 2024)}
}

Abstract

This paper presents the Fennec Adaptive Cooling Algorithm (FACA), a novel metaheuristic inspired by the thermoregulation strategies of the Fennec fox, a species native to the Algerian desert. This algorithm leverages the adaptive cooling mechanisms of the Fennec fox to balance exploration and exploitation in the optimization process. We detail the development and implementation of FACA, showcasing its application to a warehouse location problem. The algorithm's effectiveness is demonstrated through comparative analysis with other established metaheuristics, highlighting FACA's potential in achieving optimal solutions while satisfying logistical constraints. This research not only introduces a new optimization tool but also underscores the importance of local biodiversity as a source of inspiration for solving practical problems.

Keywords

Metaheuristics ; Nature ; inspired Algorithms ; Algerian Biodiversity ; Fennec Fox ; Thermoregulation ; Optimization ; Warehouse Location Problem