Paper Title:
Learning the Distribution Characteristics of Critical Machines in Production Scheduling Problems
  Abstract

A critical machine identification algorithm is proposed for the job shop scheduling problem in which the total tardiness must be minimized. An optimization-based procedure is devised to learn the distribution characteristics of critical machines in a specific scheduling instance. The proposed simulated annealing algorithm optimizes the scheduling problem after the capacity constraints for each machine are modified. A genetic algorithm based on combined dispatching rules is designed to verify the effectiveness of the proposed methodology.

  Info
Periodical
Chapter
Chapter 1: Surface Engineering/Coatings
Edited by
Prasad Yarlagadda, Yun-Hae Kim, Zhijiu Ai and Xiaodong Zhang
Pages
142-145
DOI
10.4028/www.scientific.net/AMR.337.142
Citation
R. Zhang, "Learning the Distribution Characteristics of Critical Machines in Production Scheduling Problems", Advanced Materials Research, Vol. 337, pp. 142-145, 2011
Online since
September 2011
Authors
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Xiao Qiang Xu, De Ming Lei
Chapter 5: Applied Technologies, Networks and Information Engineering
Abstract:Interval job shop scheduling problem with flexible preventive maintenance is considered and an multi-objective swarm-based neighborhood...
189
Authors: S. Gobinath, C. Arumugam, G. Ramya, M. Chandrasekaran
Chapter 2: Intelligent Algorithms and Industry Development, its Applications for Manufacturing Engineering and Automation
Abstract:The classical job-shop scheduling problem is one of the most difficult combinatorial optimization problems. Scheduling is defined as the art...
176
Authors: Xiao Xia He, Chun Yao, Qiu Hua Tang
Chapter 14: Product Design, Planning, Projects Management and Industrial Engineering
Abstract:The scheduling of the single machine is of major importance in applications. The focus of this work is to analyze the scheduling problems in...
1641