Title :
Evolutionary scheduling with rescheduling option for sudden machine breakdowns
Author :
Hasan, S. M Kamrul ; Sarker, Ruhul ; Essam, Daryl
Author_Institution :
Sch. of Eng. & IT, Univ. of New South Wales at ADFA, Canberra, ACT, Australia
Abstract :
The job scheduling problem (JSP) is considered as one of the complex combinatorial optimization problems. In this paper, we have developed a hybrid Genetic Algorithm (HGA), which improves the performance of GAs when solving JSPs. We have also modified the developed algorithm to study JSPs under the machine unavailability condition. We have considered two types of machine unavailability. Firstly, where the unavailability information is available in advance (predictive) and, secondly, where the information is known after a real breakdown (reactive). We have shown that the revised schedule is mostly able to recover if the disruptions occur during the early stages of a schedule.
Keywords :
condition monitoring; genetic algorithms; job shop scheduling; complex combinatorial optimization problem; evolutionary scheduling; hybrid genetic algorithm; job scheduling problem; sudden machine breakdown; Algorithm design and analysis; Biological cells; Electric breakdown; Maintenance engineering; Optimal scheduling; Schedules; Scheduling; Disruption; Genetic Algorithm; Hybrid Genetic Algorithm; Job Scheduling; Makespan;
Conference_Titel :
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6909-3
DOI :
10.1109/CEC.2010.5586374