Hybrid Metaheuristics for Industry 5.0 Multi-Objective Manufacturing and Supply Chain Optimization
Bezoui, Madani Turki Almaktoom, Abdulaziz Bounceur, Ahcène Mian Qaisar, Saeed Chouman, Mervat
Bezoui, Madani
Turki Almaktoom, Abdulaziz
Bounceur, Ahcène
Mian Qaisar, Saeed
Chouman, Mervat
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2024-03-21
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Abstract
This paper explores the transition to Industry 5.0, highlighting its focus on sustainable, human-centred and resilient industrial progress. In this new era, the integration of advanced technology with human expertise is crucial, emphasising the importance of balancing efficiency, cost, quality, and sustainability. At the heart of this research is Multi-Objective Optimisation (MOO), which is used to address the complex challenges of modern manufacturing systems. We propose an innovative approach that combines mathematical modelling with swarm intelligence to tackle complex optimisation problems. A detailed Multi-Objective Mixed Integer Linear Programming (MILP) model is developed and its effectiveness is demonstrated through the application of Multi-Objective Particle Swarm Optimisation (MOPSO). The study compares the performance of MOPSO with traditional optimisation methods using synthetic data analysis. The results not only demonstrate the potential of MOPSO in modern manufacturing, but also set the stage for future research to integrate human ergonomics into the optimization framework, thereby contributing to the holistic advancement of Industry 5.0.
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Effat University