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An agent-based cooperative co-evolutionary framework for optimizing the production planning of energy supply chains under uncertainty scenarios

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  • Chen, Shiyu
  • Ma, Chiye
  • Wang, Wei
  • Zio, Enrico

Abstract

Nowadays, energy and power companies compete to get the raw materials and equipment they need on time, as project times lengthen, costs spiral, stock-out continues to plague plans to a decarbonized energy future. The risks reflect the impact of uncertainty and volatility on the resilience of the supply chains. Therefore, there is a need for the enhancement of the production planning in Energy Supply Chains (ESCs), as it enables affordable energy supplies and supports the companies transition to a clean, secure and sustainable energy mix. This study aims to understand the interactive behavior among individuals and optimize their production planning under uncertainty scenarios. In particular, we propose a novel framework to couple an Agent-based Modelling (ABM) and a Co-evolutionary Algorithm (CEA), to realize its capacity to solve a Many-objective Optimization Problem (MaOP) where the profits of multiple agents are concurrently maximized in their interactive transaction processes under normal conditions and uncertain disruption events.

Suggested Citation

  • Chen, Shiyu & Ma, Chiye & Wang, Wei & Zio, Enrico, 2024. "An agent-based cooperative co-evolutionary framework for optimizing the production planning of energy supply chains under uncertainty scenarios," International Journal of Production Economics, Elsevier, vol. 277(C).
    • Handle: RePEc:eee:proeco:v:277:y:2024:i:c:s0925527324002561
    DOI: 10.1016/j.ijpe.2024.109399
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