A Simulation-Based Multi-Objective Optimization Framework for the Production Planning in Energy Supply Chains

The work presents a simulation-based Multi-Objective Optimization (MOO) framework for efficient production planning in Energy Supply Chains (ESCs). An Agent-based Model (ABM) that is more comprehensive than others adopted the literature developed to simulate agent’s uncertain behaviors and transaction processes stochastically occurring dynamically changing ESC structures. These are important realistic characteristics rarely considered. simulation embedded into Non-dominated Sorting Genetic Algorithm (NSGA-II)-based optimization scheme identify Pareto solutions which total profit maximized disequilibrium among its profits minimized, while uncertainty accounted by Monte Carlo (MC) sampling. oil gas model with five layers considered show proposed capability of enabling management sustained considering interactions structure.