Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.cie.2007.06.024
Title: Integration of genetic algorithm and Gantt chart for job shop scheduling in distributed manufacturing systems
Authors: Jia, H.Z. 
Fuh, J.Y.H. 
Nee, A.Y.C. 
Zhang, Y.F. 
Keywords: Gantt chart
Genetic algorithm
Production scheduling
Issue Date: Sep-2007
Source: Jia, H.Z.,Fuh, J.Y.H.,Nee, A.Y.C.,Zhang, Y.F. (2007-09). Integration of genetic algorithm and Gantt chart for job shop scheduling in distributed manufacturing systems. Computers and Industrial Engineering 53 (2) : 313-320. ScholarBank@NUS Repository. https://doi.org/10.1016/j.cie.2007.06.024
Abstract: In a distributed manufacturing environment, jobs in a batch could usually be manufactured in several available factories and thus have multiple alternative process plans. This paper presents a new approach to determine good combinations of factories (process plans) to manufacture the jobs and in the meantime generate good operation schedules. A genetic algorithm (GA), integrated with Gantt chart (GC), is proposed to derive the factory combination and schedule. The integration of GA-GC is proved to be efficient in solving small-sized or medium-sized scheduling problems for a distributed manufacturing system. Multiple objectives can be achieved, including minimizing makespan, job tardiness, or manufacturing cost. An illustrative example is given to demonstrate and evaluate the performance of the GA-GC approach. © 2007.
Source Title: Computers and Industrial Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/60574
ISSN: 03608352
DOI: 10.1016/j.cie.2007.06.024
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