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Enterprise Production & Sale Management System and Design & Implementation of Production Scheduling Algorithm

Author: YangFan
Tutor: ZhouChengPing
School: Huazhong University of Science and Technology
Course: Pattern Recognition and Intelligent Systems
Keywords: Job Shop Scheduling Flexible Target Optimization Genetic Algorithms
CLC: TP311.52
Type: Master's thesis
Year: 2007
Downloads: 99
Quote: 1
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Abstract


With the development of economic globalization , the increasingly competitive market , manufacturing enterprises in order to win in the competition , the need to improve the traditional production management mode . Production Scheduling is the core content of the production management and key technologies . Effective method of scheduling and optimization plays an important role in the research and application of technology , manufacturing enterprises to improve production efficiency , reduce production costs , and thus more and more attention of scholars . In this paper, the background of a manufacturing enterprise , applied research on job shop scheduling problem . First , based on comprehensive shop scheduling problem situation at home and abroad , combined with the characteristics and development trend of job shop operations , a thorough and systematic study of the production job shop scheduling problem . The comparative analysis of the existing variety of algorithms for solving Job shop scheduling problem , determine as the main means of genetic algorithms . Then discussed and analyzed the current situation of the enterprise system design goals , and a brief introduction of the composition of the structure of the system and of the completion of the development tasks , and focus on the analysis of the actual production scheduling problem . Break through the limitations of classical shop scheduling problem , advanced manufacturing plant optimization of scheduling problems with routing flexibility . Taking into account the characteristics shop scheduling multi-objective and punctuality requirements of modern production , mathematical optimization model for the establishment of a multi-objective flexible job shop scheduling problem . Finally , for multi-objective flexible job shop scheduling model , the proposed multi-objective optimization genetic algorithm based machine variable constraints . The algorithm uses a process the order and said that the machine selected 2D encoding , multi-objective optimization function measure , through targeted genetic manipulation of the search space for expansion of the diversity of the offspring and algorithms . The simulation results show the feasibility of the proposed algorithm .

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