A Multi-objective ε-Constraint Optimization of Coal Supply Chain Performance Considering Customer Satisfaction in Multi-layer Logistics Networks

This study addresses the integration of customer satisfaction into coal supply chain optimization. The research identifies a gap in the comprehensive evaluation of customer satisfaction impacts through a critical review of existing supply chain management practices and multi-objective optimization approaches. To bridge this gap, the study introduces an innovative application of the ε-constraint method to develop a mathematical model that maximizes enterprise profit and enhances customer satisfaction. The model incorporates a hierarchical logistics network, enabling detailed analysis of coal mine production, transportation allocation, inventory management, and delivery strategies. Using a large coal enterprise as a case study, numerical simulations conducted in MATLAB’s intlinprog solver (Optimization Toolbox) generate the Pareto frontier under varying levels of customer satisfaction, thereby illustrating the inherent trade-offs between profitability and service quality. The results indicate that while moderate improvements in customer satisfaction (from 64.3% to 67.5%) lead to a gradual decline in profits, exceeding a critical threshold causes a significant drop in profitability. The primary contribution of this work lies in its novel integration of the ε-constraint method with a multi-tier logistics structure, providing a strategic framework for optimizing coal production and distribution, with customer satisfaction as a central objective.