Synergizing efficiency, flexibility, and sustainability of value chain to optimization of energy consumption.

Document Type : Research Paper

Authors

1 Department of Industrial Engineering, Lahijan Branch, Islamic Azad University, Lahijan, Iran

2 Industrial Engineering Department, Alzahra University, Deh Vanak, Tehran, Iran

3 Department of Industrial Engineering, sari Branch, Islamic Azad University, sari, Iran

4 Department of Industrial Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran

Abstract

In response to the dynamic requirements of contemporary businesses, this research delves into the imperative for organizations to optimize the efficiency, flexibility, and sustainability of their value chains, especially concerning energy consumption. The study introduces a multi-objective model meticulously designed to align efficiency, flexibility, and sustainability, aiming for a well-balanced and optimal energy consumption profile throughout the entire value chain. The optimization process employs multi-objective programming, with the overarching objective of maximizing minimum levels of flexibility, stability, and efficiency while minimizing the maximum energy consumption. Addressing the intricacies of large-scale multi-objective models, the research proposes a two-phase Multi-Objective Evolutionary Algorithm (MOEA), leveraging the strengths of NSGA-II and MOACO. The effectiveness of the proposed model is substantiated through a series of numerical experiments and sensitivity analyses, providing conclusive evidence of its capability to navigate the complexities of optimizing energy consumption in value chains. Furthermore, the performance of the proposed algorithm is affirmed through the examination of indicators such as generation gap (GD), high volume (HV), error ratio (ER), and non-dominant vector generation (ONVG). Hence, the presented model and solution algorithm are suitable for real-world problems.

Keywords

Main Subjects


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Articles in Press, Accepted Manuscript
Available Online from 17 February 2024
  • Receive Date: 17 February 2024
  • Accept Date: 17 February 2024