Optimizing Supply Chain Efficiency Using Innovative Goal Programming and Advanced Metaheuristic Techniques

Author:

Douaioui Kaoutar1ORCID,Benmoussa Othmane2ORCID,Ahlaqqach Mustapha3ORCID

Affiliation:

1. Laboratory of Engineering, Industrial Management and Innovation, Faculty of Sciences and Techniques, Hassan 1st University, Settat 26000, Morocco

2. Euromed Polytechnic School, Euromed University of Fes, Fez 30030, Morocco

3. Laboratory of Advanced Research in Industrial and Logistic Engineering, National School of Electricity and Mechanics, Hassan II University of Casablanca, Casablanca 20202, Morocco

Abstract

This paper presents an optimization approach for supply chain management that incorporates goal programming (GP), dependent chance constraints (DCC), and the hunger games search algorithm (HGSA). The model acknowledges uncertainty by embedding uncertain parameters that promote resilience and efficiency. It focuses on minimizing costs while maximizing on-time deliveries and optimizing key decision variables such as production setups, quantities, inventory levels, and backorders. Extensive simulations and numerical results confirm the model’s effectiveness in providing robust solutions to dynamically changing supply chain problems when compared to conventional models. However, the integrated model introduces substantial computational complexity, which may pose challenges in large-scale real-world applications. Additionally, the model’s reliance on precise probabilistic and fuzzy parameters may limit its applicability in environments with insufficient or imprecise data. Despite these limitations, the proposed approach has the potential to significantly enhance supply chain resilience and efficiency, offering valuable insights for both academia and industry.

Funder

Al-Khwarizmi Programme

Scientific and Technical Research

Agency for Digital Development (ADD

Moroccan Ministry of Higher Education

Publisher

MDPI AG

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