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A Multiobjective Optimization Model for a Dynamic and Sustainable Cellular Manufacturing System under Uncertainty.

Javad Jafarzadeh¹, Hossein Amoozad Khalili², Naghi Shoja³

¹Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.

Computational Intelligence and Neuroscience

|October 3, 2022

Summary

This study introduces a sustainable manufacturing model for dynamic cellular systems, optimizing cost, CO2 emissions, and customer satisfaction under uncertainty. The MOGWO algorithm demonstrated superior performance compared to NSGA-II and exact methods.

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Area of Science:

Operations Research
Industrial Engineering
Sustainable Manufacturing

Background:

Cellular manufacturing is widely adopted, but integrating sustainability is crucial.
Existing research often overlooks comprehensive sustainability (economic, environmental, social).
Growing environmental concerns necessitate incorporating CO2 emissions and customer satisfaction into manufacturing models.

Purpose of the Study:

To develop a multiobjective sustainable mathematical model for dynamic cellular manufacturing systems.
To address uncertainty in parameters using fuzzy logic.
To optimize cost, CO2 emissions, and product shortages (customer satisfaction).

Main Methods:

A multiobjective mathematical model was formulated.
The model was validated using GAMS software with CPLEX solver and the epsilon constraint method.
Two meta-heuristic algorithms, NSGA-II and MOGWO, were implemented in MATLAB for larger problems.
Taguchi method was used for algorithm parameter tuning.
Statistical analysis was performed using Minitab software.

Main Results:

The MOGWO algorithm outperformed the NSGA-II algorithm and the exact solution method (GAMS).
Performance comparison of algorithms was based on various evaluation indicators.
Statistical analysis confirmed the significance of the differences between algorithms.

Conclusions:

The proposed model effectively integrates economic, environmental, and social aspects of sustainability in dynamic cellular manufacturing.
The MOGWO algorithm is a highly effective approach for solving complex sustainable dynamic cellular manufacturing problems.
This research provides a robust framework for enhancing sustainable manufacturing practices.