Earticle

초록

영어

Considering the production scheduling problem of processes industry and the disadvantages of conventional differential evolution algorithm, a method of production scheduling oriented to energy consumption optimization for process industry is proposed in this paper, which is based on self-adaptive differential evolution algorithm. Based on the analysis of production scheduling problems for processes industry, a production scheduling model is established, whose goal is to obtain the minimum of total process energy consumption. Since the basic differential evolution algorithm has the disadvantage that the search performance is very sensitive to the parameter settings, the self-adaptive control evolution strategy are used to control the parameters scale factor(F) and crossover probability(CR) to improve the global search ability and convergence speed. A practical production scheduling problem is taken as an example here, the established model and self-adaptive differential evolution algorithm are adopted to realize scheduling simulation with the minimum total process energy consumption. The simulation results show that the production scheduling method oriented to energy consumption optimization is superior to the production scheduling method oriented to process time optimization, and it can realize the goal of reducing energy consumption.

목차

Abstract
 1. Introduction
 2. Description of Production Scheduling Oriented to Energy Consumption Optimization for Process Industry
  2.1 Definition of Correlated Variables
  2.2 Mathematical Model of Production Scheduling Oriented to Energy Consumption Optimization for Process Industry
 3. DE Algorithm Design of Production Scheduling Oriented to Energy Consumption Optimization
  3.1 Design of Differential Encoding
  3.2 Design of Self-adaptive DE Algorithm
  3.3 Fitness Function
  3.4 Realization of Self-adaptive DE Algorithm
 4. Production Scheduling Simulation Based on Self-adaptive DE Algorithm
  4.1 Description of a Production Scheduling Example
  4.2 Simulation Results and Discussion
 5. Conclusions and Future Work
 Acknowledgments
 References

키워드

저자

• Lieping Zhang [ Guangxi Key Laboratory of New Energy and Building Energy Saving, Guilin University of Technology, Guilin, 541004, China, College of Mechanical and Control Engineering, Guilin University of Technology, Guilin, 541004, China ]
• Yingxiong Luo [ College of Information Science and Engineering, Guilin University of Technology, Guilin, 541004, China ]
• Yu Zhang [ Guangxi Key Laboratory of New Energy and Building Energy Saving, Guilin University of Technology, Guilin, 541004, China, College of Mechanical and Control Engineering, Guilin University of Technology, Guilin, 541004, China ]
• Gang Song [ College of Information Science and Engineering, Guilin University of Technology, Guilin, 541004, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605