| 초록 |
In this paper, we develop an extended supply chain optimization model for refinery industry. It consists of several echelons because the supply chains from crude oil suppliers to customers involve storage and blending tank network before Crude Distillation Unit, and product distribution network after the CDU. Accordingly, it has a large number of integer decision variables, which cause complexity for solving a Mixed Integer Linear Programming problem. Additionally, we consider transportation delays of materials that make the MILP problem more difficult to solve because the time horizon must be extended. Since the proposed problem cannot be solved in reasonable time due to the many integer variables, we propose a technique to decompose the problem. We use a rolling horizon approach. However, it is not a new approach originally. So we add aggregation concept into the rolling horizon approach. |
