Title :
A Heuristic Algorithm for Large-Scale Job Shop Scheduling Based on Operation Decomposition Using Bottleneck Machine
Author :
Zhai, Yingni ; Sun, Shudong ; Wang, Junqiang ; Guo, Shihui
Author_Institution :
Key Lab. of Contemporary Design & Integrated Manuf. Technol., Northwestern Polytech. Univ., Xi´´an, China
Abstract :
A new heuristic algorithm for large-scale job shop scheduling problem is proposed based on operation decomposition using bottleneck machine. It detects bottleneck machine by orthogonal experiment. Based on the operations which are processed on the bottleneck machine, the large-scale job shop scheduling problem is divided into three sub-problems: the scheduling problem of the operations on bottleneck machine, pre-bottleneck machines and post-bottleneck machines. The operations on bottleneck machine are first scheduled by dispatching rules, and the other two sub-problems are solved by genetic algorithm to subordinate the schedule of the operations on bottleneck machine. A number of simulation results shown that the scheduling strategy and technique for the problem can improve the computing efficiency and quality of the solution.
Keywords :
design of experiments; genetic algorithms; heuristic programming; job shop scheduling; bottleneck machine; dispatching rules; genetic algorithm; heuristic algorithm; large-scale job shop scheduling strategy; operation decompositon; orthogonal experiment; Algorithm design and analysis; Dispatching; Equations; Job shop scheduling; Processor scheduling; Schedules;
Conference_Titel :
Management and Service Science (MASS), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5325-2
Electronic_ISBN :
978-1-4244-5326-9
DOI :
10.1109/ICMSS.2010.5576038