Circular Energy Supply Chain Design for Sustainable Manufacturing: A Study on Intelligent Algorithms and Multi-Objective Optimization

Abstract

Under the dual challenges of climate change and resource constraints, manufacturing parks are increasingly required to coordinate energy supply, material recovery, and emission reduction in an integrated manner. However, many existing studies focus on either one-way energy supply or isolated emission-control measures, while the joint design of renewable energy use, energy storage, waste heat recovery, and material circulation remains insufficiently explored. To address this issue, this study develops a scenario-based circular energy supply chain design framework for sustainable manufacturing parks. A multi-objective mixed-integer linear programming model is formulated to balance economic cost, carbon emissions, and local employment. To improve computational tractability, a hybrid solution framework combining K-means scenario reduction, NSGA-II, and variable neighborhood search is proposed.A numerical case is constructed based on a representative manufacturing park setting, public meteorological characteristics, literature-based technical parameters, and synthetic load profiles calibrated to typical industrial operating patterns. The proposed approach is compared with a commercial solver on small- and medium-scale benchmark instances and is further tested on larger instances under a fixed computational time limit. The results show that the circular design strategy can reduce total system cost and carbon emissions in the constructed benchmark scenario, while increasing local employment opportunities. Sensitivity analyses on carbon price, renewable-energy equipment cost, and load outliers further illustrate the influence of key parameters on system configuration. The findings provide a reproducible modeling and computational framework for preliminary planning of circular energy and material networks in manufacturing parks, rather than a direct validation of a specific real industrial project.