Improved particle swarm optimization algorithm for optimum charge plan for steelmaking-continuous casting production scheduling

An optimum furnace charge plan model for steelmaking continuous casting planning and scheduling is presented. An improved particle swarm optimization with disturbances is presented to solve the optimum charge plan problem. In order to find the premature convergence, a mature factor and the efficiency step of iteration are also introduced. Simulations have been carried and the results show that the improved PSO has good performance than the standard PSO. This improved PSO has been used to solve the optimum charge plan problem. The computation with practical data shows that the model and the solving method are very effective.

I. Introduction

Iron and steel industrial is an essential and sizable sector for industrialized economies. Since it is capital and energy extensive, companies have been putting consistent emphasis on technology advances in the production to increaseproductivity and to save energy. The modern integrated process of steelmaking, continuous casting and hot rolling directly connects the steelmaking furnace, the continuous caster and the hot rolling mill with hot metal flow and makes a synchronized production. However, it also brings new changes for production planning and scheduling. For steel making process, the main work is to arrange the charge plan and cast plan. The basic unit of steelmaking is the charge. To make the charge plan, the following conditions are needed: 1)

Steel grades must be the same,

2)

steel thickness of the charges must be equal.,

3)

the width of armor plate must be the same.,

4)

the consignment date must be near,

5)

90% furnace capacity ≤ total weight in each furnace ≤ 100% furnace capacity.