Steel-making Production Scheduling Research Based On Immune Algorithm And Scatter Search

Production scheduling is the key element in manufacturing enterprises, and scientifically formulating and executing it can shorten production cycle, reduce inventories of work in process, decrease the production cost and improve enterprises competitive power in the market. Steel-making production scheduling is the application of production scheduling theory in the steel-making circumstance, and it should consider several aspects such as technological requirements of steel-making, computer system and management techniques, and then make it become auxiliary decision-making tools for the steel-making process by establishing reasonable scheduling model and scheduling scheme.Immune algorithm (IA) and scatter search (SS) are population-based evolutionary algorithms which have strong global search ability, but they have many differences in evolution mechanism, search strategy and so on. The paper discusses several scheduling problem in steel-making production, analyzes their scheduling needs, presents their mathematical models, develops effective optimization algorithms to search optimal and near-optimal solutions, and then applies industrial production data to illustrate the effectiveness of these algorithms. The main objective of the paper is providing effective and reasonable scheduling scheme to steel-making industries and providing theoretical foundation for the improvement of steeling-making scheduling techniques. The main research achievements of the paper are:Firstly, the paper has studied the cost-driven flowshop scheduling problem. The paper presents a cost-driven model of the flowshop scheduling problem (FSP) by involving economic index into the problem. The cost model is developed in terms of a combination of multi-dimensional costs generated from product transitions, revenue loss, earliness / tardiness penalty, and so on. A new immune algorithm, called IA-ATS, combines the strong global search ability of IA with the strong local search ability of adaptive tabu search (ATS). The experimental simulation tests show the validity of the cost-driven model and the effectiveness of the hybrid IA-ATS algorithm.Secondly, the paper has studied continuous casting scheduling problem (CCSP). The paper presents a hybrid flow shop scheduling model for the problem, which takes continuous casting and waiting time of furnaces as constraints, and takes total flowtime of process as objective function. A production scheduling method which combines heuristic rule and linear programming is presented after considering the solving complexity of the problem, and then embedded into the IA-ATS algorithm. The experimental results show that the algorithm is an effective method for the CCSP. It can realize continuous casting during working process, improve the equipment usage efficiency, reduce the waiting time between different operations, reduce materials and energy consumption, and consequently reduce production cost and improve the profit of steel-making enterprises.Thirdly, the paper has studied hot rolling scheduling problem. We apply prize-collecting vehicle routing problem to present the mathematical model of hot rolling scheduling problem after considering switchover cost of roller and customer service level. The mathematical model combines order selection with slab sequencing, and takes reducing the width, gauge and hardness jump penalty and satisfying delivery date as scheduling objectives. And then, a new scatter search algorithm (SS-IEO) which combines scatter search (SS) with improved extremal optimization (IEO) is proposed. The hybrid SS-IEO algorithm combines the strong global search ability of SS with the strong local search ability of IEO and mitigates their disadvantages. Several experiment simulations of steel-making enterprise production instances are conducted to illustrate the effectiveness of algorithm. The computational results show that the algorithm can get satisfied scheduling solutions in reasonable running time and is superior to IA-ATS, but has less generality than IA-ATS.Lastly, the paper studied the cold rolling scheduling problem. Skin pass mill scheduling problem is a very complex problem which has coupling between coil parameters and machine performance. In chapter 5, the paper presents an effective decomposition-combination mechanism which divides the complex scheduling problem into three tractable sub-problems: clusting problem, K- constrained shortest path problem (K-CSSP), and multi-phase shortest path problem. A mixed strategy which combines SS-IEO with dynamic programming (DP) is presented: firstly assigning orders into different stages, and then solving the K-CSSP of each stage by SS-IEO, and combining the solutions of sub-problems into a feasible solution by DP at last phase. The computational experiments demonstrate the effectiveness of the proposed strategy.