Reactive scheduling in a job shop where jobs arrive over time

Authors:
Li Nie;Liang Gao;Peigen Li;Xinyu Shao
Affiliations:
The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science & Technology, Wuhan 430074, People's Republic of China and School of Mechanical & Electro ...;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science & Technology, Wuhan 430074, People's Republic of China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science & Technology, Wuhan 430074, People's Republic of China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science & Technology, Wuhan 430074, People's Republic of China
Venue:
Computers and Industrial Engineering
Year:
2013

Citing 11
Cited 0

Genetic learning of dynamic scheduling within a simulation environment

Computers and Operations Research - Special issue: heuristic, genetic and tabu search
A New Algorithm for Preemptive Scheduling of Trees

Journal of the ACM (JACM)
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Optimal On-Line Algorithms for Single-Machine Scheduling

Proceedings of the 5th International IPCO Conference on Integer Programming and Combinatorial Optimization
Rescheduling Manufacturing Systems: A Framework of Strategies, Policies, and Methods

Journal of Scheduling
Rapid Modeling and Discovery of Priority Dispatching Rules: An Autonomous Learning Approach

Journal of Scheduling
Introduction to genetic programming

Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Evolving dispatching rules using genetic programming for solving multi-objective flexible job-shop problems

Computers and Industrial Engineering
Training a neural network to select dispatching rules in real time

Computers and Industrial Engineering
Dynamic scheduling with genetic programming

EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
Scheduling on identical machines: How good is LPT in an on-line setting?

Operations Research Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

The paper considers the dynamic job shop scheduling problem (DJSSP) with job release dates which arises widely in practical production systems. The principle characteristic of DJSSP considered in the paper is that the jobs arrive continuously in time and the attributes of the jobs, such as the release dates, routings and processing times are not known in advance, whereas in the classical job shop scheduling problem (CJSSP), it is assumed that all jobs to be processed are available at the beginning of the scheduling process. Reactive scheduling approach is one of the effective approaches for DJSSP. In the paper, a heuristic is proposed to implement the reactive scheduling of the jobs in the dynamic production environment. The proposed heuristic decomposes the original scheduling problem into a number of sub problems. Each sub problem, in fact, is a dynamic single machine scheduling problem with job release dates. The scheduling technique applied in theproposed heuristic is priority scheduling, which determines the next state of the system based on priority values of certain system elements. The system elements are prioritized with the help of scheduling rules (SRs). An approach based on gene expression programming (GEP) is also proposed in the paper to construct efficient SRs for DJSSP. The rules constructed by GEP are evaluated in the comparison of the rules constructed by GP and several prominent human made rules selected from literatures on extensive problem sets with respect to various measures of performance.