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|Title:||Integration of genetic algorithm and Gantt chart for job shop scheduling in distributed manufacturing systems||Authors:||Jia, H.Z.
|Issue Date:||Sep-2007||Citation:||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|
|Appears in Collections:||Staff Publications|
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