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Related Experiment Video

Updated: May 29, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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Fuzzy multi-objective optimization model to design a sustainable closed-loop manufacturing system.

Sajida Kousar1, Asma Alvi1, Nasreen Kausar2

  • 1Department of Mathematics and Statistics, International Islamic University, Islamabad, Pakistan.

Peerj. Computer Science
|February 3, 2025
PubMed
Summary

This study introduces a sustainable manufacturing system to reduce energy consumption and carbon dioxide (CO2) emissions. The developed fuzzy multi-objective model effectively minimizes costs and environmental impacts in industrial settings.

Keywords:
Closed-loop systemMulti-objective optimizationSustainability

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Area of Science:

  • Industrial Engineering
  • Environmental Science
  • Operations Research

Background:

  • Growing bipartisan concern for environmental conservation and Sustainable Development Goals (SDGs) drives industrial innovation.
  • Efforts to reduce energy consumption and carbon dioxide (CO2) emissions are critical for sustainable enterprise operations.
  • Existing manufacturing systems face challenges in optimizing for both economic and environmental factors.

Purpose of the Study:

  • To propose an environmentally friendly manufacturing system that minimizes environmental impacts.
  • To develop a sustainable manufacturing process accounting for energy consumption and CO2 emissions from all sources.
  • To formulate a multi-objective mathematical model addressing financial and environmental constraints.

Main Methods:

  • Formulation of a multi-objective mathematical model to minimize costs, energy consumption, and CO2 emissions.
  • Development of a fuzzy multi-objective model to handle unpredictable real-world input parameters.
  • Scenario-based approach to test the validity and effectiveness of the proposed ecological industrial design.

Main Results:

  • The proposed manufacturing system demonstrates high reliability and applicability.
  • The fuzzy multi-objective model effectively manages uncertainties in real-world manufacturing parameters.
  • The study validates the effectiveness of the developed techniques for sustainable industrial design.

Conclusions:

  • The developed environmentally friendly manufacturing system offers a viable solution for reducing industrial environmental footprints.
  • Fuzzy multi-objective optimization is a robust approach for sustainable manufacturing under uncertainty.
  • The findings support the integration of sustainability principles into industrial processes to achieve SDGs.