Dissertation > Excellent graduate degree dissertation topics show

Research and Application of Single-Stage Multi-Product Batch Scheduling Based on Quantum Genetic Algorithm

Author: JiangJiaYing
Tutor: WangWanLiang;XuXinLi
School: Zhejiang University of Technology
Course: Control Theory and Control Engineering
Keywords: quantum genetic algorithm real-code vat scheduling batch scheduling
CLC: TP18
Type: Master's thesis
Year: 2011
Downloads: 24
Quote: 0
Read: Download Dissertation

Abstract


Single-stage multi-product batch process is one kind of common production lines inchemical industry. However, the scheduling of single-stage multi-product batch process is muchmore difficult than the others because of its characteristics like equipment handling flexibility,limited batch quantity and noticeable switching cost. During the past two decades, the short-termscheduling model has attracted widespread attention and research. As a new intelligenceoptimization algorithm, quantum genetic algorithm (QGA) is gradually becoming a hot spot, dueto its advantage of population diversity, being good at exploring and being easy to mix withother algorithms. This paper presents the relevant studies focused on the application of QGA inthe single-stage multi-product batch scheduling. The main work is as follows:(1) An improved QGA (Real-Coded Quantum Genetic Algorithm, RQGA) is proposed toagainst the defects of long-time convergence and easily falling into quantum“length disaster”inthe basic QGA. Firstly, an approximation operator is constructed to replace the traditionalrevolving door. It avoids the cumbersome table look-up operation and shortens the convergencetime effectively. Secondly, omitting quantum observation and encoding the quantum directly isadopted. It overcomes the "length disaster" caused by large number of quantum variables andexpands the application scope of the quantum genetic algorithm.(2) Discussion on the application of RQGA in single-stage multi-production batch process.A mixed integer linear programming model with the goal of maximizing production profits isconstructed, and through real coding to achieve the correspondence between quantum individualand process sequencing. Finally, typical example is simulated and the results have verified thevalidity and feasibility of RQGA in single-stage multi-product batch scheduling problem.(3) For the vat scheduling problem in dyeing and printing industry, a MILP model based onthe time slot ideas is established. It meets the due date condition as well as the goal of minimizing production cost, and quantum genetic algorithm is adopted to solve it. In the solutionprocess, a new order-consolidating and order-splitting method is used. The method is thatconsolidates and splits orders directly after counting the sum of the same products notconsidering the source of the orders, so the solution process is simplified. Finally, simulationresults indicate validity and feasibility of the model, as well as show the practicability ofquantum genetic algorithm in vat scheduling.Finally, a summary is made and some future works are presented.

Related Dissertations

  1. Research on DNA Encoding Based on Quantum Computing,Q75
  2. Agent-based negotiation strategy production scheduling batches,TP18
  3. Study on Optimization Modeling and Intelligent Control of Alcohol-based Fuel Boiler Combustion System,TK223.2
  4. Research of QGA on the Mechanical Optimization Problems,TP18
  5. The Application of an Improved PSO Based on the Quantum Genetic Algorithm in the Submersible Path-planning,TP18
  6. Research on Uncertain Production Scheduling Based on Improved Quantum Genetic Algorithm,TP18
  7. Job Shop Scheduling Based on Hybrid Genetic Algorithm,TP18
  8. Research on the Gas Forecast Model Owing to That BP Neural Networks and Quantum Genetic Algorithm,TP183
  9. Design on Real Code Simulation Platform of Wireless Sensor Network Based on OMNeT++,TN929.5
  10. Improvement and Application in Routing Problem of Quantum Genetic Algorithm,TP18
  11. Research on Uncertain Information Processing and Dynamic Judgement in Transmission Network Planning,TM715
  12. On Job-shop Scheduling by Improved Quantum Genetic Algorithm,TP18
  13. Quantum Genetic Algorithm and Its Application in Multiple Sequence Alignment,TP18
  14. Medical image sequences motion estimation,R318
  15. A Study on Improved Quantum Genetic Algorithm,TP18
  16. On Several Problems of Batch Scheduling, Scheduling with Rejection and Scheduling with Discretely Processing Times,O223
  17. The Control Method and Simulation Research of Urban Intelligent Traffic Signal,U491.5
  18. China 's personal credit system building,F832
  19. Based on Quantum Genetic Algorithm Bayesian network structure learning,TP183
  20. The Research on Intelligent Scheduling of Production Planning Based on Quantum Genetic Algorithm,TP18
  21. Research and Design of Optimized Production Planning of Vat System in Dyeing Yarn Workshop,TS193

CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory
© 2012 www.DissertationTopic.Net  Mobile