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Genetic Algorithm for Solving a Class of Order Scheduling Problem

Author: XueZhiRong
Tutor: WangXiuLi
School: Nanjing University of Technology and Engineering
Course: Management Science and Engineering
Keywords: Order Scheduling Total (Weighted) Completion Time Genetic Algorithm Heuristic Rules
CLC: TP18
Type: Master's thesis
Year: 2010
Downloads: 106
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Abstract


Order scheduling problem can be simply described as:Each order includes different types of jobs, each machine can only process a particular job, and the job of each order must be a continuous process until the completion of the order, the order completion time is the maximum completion time of all jobs. Order scheduling is to study the whole completion situation of a group of jobs in an order. Many scholars have attempted to develop heuristic algorithm for order scheduling problem, and they can achieve optimum solution, while the genetic algorithm as an artificial intelligence algorithm, with adaptive, parallel and global optimization characteristics, this paper applied Genetic Algorithm to these two types of orders to solve the scheduling model in a fully dedicated environment to minimize the total completion time and minimize the total weighted completion time.The article first describes in detail the order scheduling problem, establish order scheduling mathematical model for these two characteristics of the total completion time and total weighted completion time. and completed the coding design of genetic algorithm, fitness function design, optimization choice of genetic operator parameters, genetic factors such as genetic manipulation, and use the powerful Matlab numerical computing and library functions write optimization program; Then heuristic rules on order scheduling are introduced, detailed scheduling principle for each heuristic and related examples are given; After numerical simulation, a comparative is studied between Genetic Algorithm and heuristic rules to consider situation of different number of orders and machines; the final results show that Genetic Algorithm is more effective compared with the heuristic rules for the two order scheduling models, but there are still some deficiencies, which is worth further study. Finally Genetic Algorithm in order scheduling prospect.

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CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory
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