Hierarchical Approach to Integrated Planning of Industrial Gas Supply Chains

In this article, an optimization-based framework is proposed for integrated production and distribution planning of industrial gas supply chains. The main goal is to minimize the overall cost, which is composed of raw material, product sourced from external suppliers, production, truck, and rail-car costs, while satisfying customer demands. The overall problem is formulated as a mixed-integer linear programming (MILP) model while a two-phase hierarchical solution strategy is developed to solve the resulting optimization problem efficiently. The first phase relies on truck scheduling decisions being relaxed, whereas the second phase solves the original model at reduced space by fixing product allocation as determined by phase one. Finally, an industrial-size case study is used to illustrate the applicability and efficiency of the proposed optimization framework.

Automated summary

An optimization-based framework is proposed for integrated production and distribution planning of industrial gas supply chains in order to minimize overall cost and satisfy customer demands. The framework utilizes a mixed-integer linear programming model and a two-phase hierarchical solution strategy to efficiently solve the optimization problem. The applicability and efficiency of the framework are demonstrated through an industrial-size case study.