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Butterfly Algorithm for Sustainable Lot Size Optimization

Author

Listed:
  • Zoubida Benmamoun

    (Faculty of Engineering, Liwa College of Technology, Abu Dhabi 41009, United Arab Emirates)

  • Widad Fethallah

    (National School for Applied Sciences, Abdelmalek Essaadi University, Tangier 93000, Morocco)

  • Mustapha Ahlaqqach

    (LARILE ENSEM, Hassan II University of Casablanca, Casablanca 20202, Morocco)

  • Ikhlef Jebbor

    (GS Laboratory, Sultan Moulay Slimane University, Beni Mellal 23000, Morocco)

  • Mouad Benmamoun

    (ANISSE, Faculty of Sciences, Mohammed V University in Rabat, Rabat 10170, Morocco)

  • Mariam Elkhechafi

    (ISCAE, Casablanca 27182, Morocco)

Abstract

The challenges faced by classical supply chain management affect efficiency with regard to business. Classical supply chain management is associated with high risks due to a lack of accountability and transparency. The use of optimization algorithms is considered decision-making support to improve the operations and processes in green manufacturing. This paper suggests a solution to the green lot size optimization problem using bio-inspired algorithms, specifically, the butterfly algorithm. For this, our methodology consisted of first collecting the real data, then the data were expressed with a simple function with several constraints to optimize the total costs while reducing the CO 2 emission, serving as input for the butterfly algorithm BA model. The BA model was then used to find the optimal lot size that balances cost-effectiveness and sustainability. Through extensive experiments, we compared the results of BA with those of other bio-inspired algorithms, showing that BA consistently outperformed the alternatives. The contribution of this work is to provide an efficient solution to the sustainable lot-size optimization problem, thereby reducing the environmental impact and optimizing the supply chain well. Conclusions: BA has shown that it can achieve the best results compared to other existing optimization methods. It is also a valuable chainsaw tool.

Suggested Citation

  • Zoubida Benmamoun & Widad Fethallah & Mustapha Ahlaqqach & Ikhlef Jebbor & Mouad Benmamoun & Mariam Elkhechafi, 2023. "Butterfly Algorithm for Sustainable Lot Size Optimization," Sustainability, MDPI, vol. 15(15), pages 1-21, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:15:p:11761-:d:1206895
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    References listed on IDEAS

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    Cited by:

    1. Zoubida Benmamoun & Khaoula Khlie & Mohammad Dehghani & Youness Gherabi, 2024. "WOA: Wombat Optimization Algorithm for Solving Supply Chain Optimization Problems," Mathematics, MDPI, vol. 12(7), pages 1-61, April.

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