Sustainable Steel Supply Chain Network Design under Export Taxes and Import Tariffs: A Multi-objective Stochastic Programming Framework

Abstract

This paper introduces a two-stage stochastic programming model featuring multi-objective recourse functions to address the economic, environmental, and social dimensions of sustainability in steel supply chain networks. The model integrates strategic decisions (facility location, capacity acquisition, and technology selection) with tactical material flow coordination. The dynamics of steel industry-specific characteristics are captured through multi-scale time periods, technology compatibility requirements, and sustainability metrics based on location-technology-flow configurations. Furthermore, the model incorporates export taxes and import tariffs to optimise material flows between nationwide and global networks, enabling comprehensive analysis of how these policy tools influence strategic and tactical decisions whilst impacting sustainability objectives. A solution approach is developed using the ε-constraint and Sample Average Approximation methods to address demand uncertainty and the trade-offs among multiple recourse objectives. Novel algorithms are introduced to determine the upper and lower bounds of the constrained objective functions and to form the loops of the ε-constraint method. The model's application to a real-world case study demonstrates its effectiveness in achieving balanced material flows across the steel SCN after four strategic periods. Through sustainability assessment and analysis of various tax and tariff policies, we derive eight policy insights regarding their impacts on strategic and tactical decisions. The results confirm the model's capability to generate robust solutions that effectively balance network capacity against demand patterns while achieving sustainability objectives.