Solving the Order Planning Problem at the Steelmaking Shops by Considering Logistics Balance on the Plant-Wide Process

Abstract

With regard to the characteristics of long process, multi-units, cross-logistics and batch production mode, the order planning problem at the steelmaking shop is studied with consideration of the plant-wide process logistics balance. The problem is to allocate the orders to the continuous casters over plan periods such that the semi-finished materials produced by the steelmaking process can be delivered to the downstream hot-rolling and cold-rolling processes on time at required volume. Based on the detailed analysis of unit layout characteristics of the plant-wide process and the order composition information, a hierarchical planning method is proposed to decompose the large-scale planning problem into a set of sub-problems that are sequential solved. For the order batching subproblem, we develop an integer programming model to consolidate orders with small demand into cast-lots by considering the key batching rules. The model is efficiently solved by the optimization solver of CPLEX. For the cast-lot scheduling subproblem, a novel mixed integer programming model is developed by considering the technological constraints, the facility capacity constraints, the logistics balance constraints, the inventory constraints, and the due date constraints. An improved differential evolution algorithm is proposed to solve the cast-lot scheduling subproblem. The main improvement strategy is that the superior individuals within an external archive are further enhanced through a variable neighborhood search mechanism. Computational results on random and practical instances of different scale problems verify the effectiveness of the proposed method.

Keywords

• Production planning
• logistics balance
• mixed integer programming
• differential evolution
• variable neighborhood search