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Researches on Modeling and Solving of Production Scheduling for Process Industry Based on Saving Energy

Author: LiuXiang
Tutor: ZouFengXing；ZhangXiangPing
School: National University of Defense Science and Technology
Course: Control Science and Engineering
Keywords: Process Industry Production scheduling Multi-product batch Energy consumption Genetic Algorithms Improved Memetic Algorithm
CLC: TB497
Type: Master's thesis
Year: 2008
Downloads: 159
Quote: 3
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Abstract


The process industry is the pillar industry of the national economy, and holds an important position. Production scheduling process production run command center will play an important role for improving the processes of economic and social benefits of the enterprise, improve the quality and efficiency of production scheduling. The energy consumption is a very important factor in the process of industrial production, it is not only related to the economic efficiency of enterprises, and corporate social responsibility are closely related. In the increasingly tight energy supply, rising prices at home and abroad, to carry out the study of the scheduling method to achieve energy saving, is of great significance, especially metallurgy such high energy consumption industries. This article is based on the National Natural Science Foundation of China nonferrous metallurgy process for energy saving control a number of theories and methods \scheduling method study \Selected a wide range of process industries exist parallel device, multi-product batch scheduling problem as the main object of study, a wide-ranging and in-depth research in modeling, algorithm. The research topics include: 1 study hybrid flowshop scheduling problem scheduling goal to minimize energy consumption, the use of genetic algorithm to solve; designed an adaptive genetic algorithm in order to overcome the defects of genetic algorithm; simulation results show that, since adapt genetic algorithm is better than simple genetic algorithm. Multi-product batch for the existence of a parallel device batch method; under the conditions of existence of the intermediate storage, to energy consumption minimum target, considering the various constraints, the establishment of a mathematical model. 3, for the above mathematical model, as a basic framework of a genetic algorithm, simulated annealing algorithm and tabu search algorithm embedded constitute improvements Memetic algorithm; proposed for the multi-product batch key to improved Memetic algorithm operators and parameters. 4, call Improved Memetic Algorithm Solving aluminum industrial production as the background energy conservation-oriented multi-product batch scheduling problem Memetic algorithm Memetic Algorithm results obtained with genetic algorithms and improved will improve the obtained results are compared and analyzed, verified superiority improved Memetic algorithm. Finally, a summary of the full text and look forward to the process of industrial production scheduling problem modeling techniques and solution methods need further study and practical application prospects.

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