A Novel Genetic Algorithm to Solve DFJSP Scheduling Problems  

Oleh:

Lin, Chi-Shiuan ; Chen, Chen-Fu ; Wu, Muh-Cherng

Jenis: Article from Proceeding
Dalam koleksi: The 14th Asia Pacific Industrial Engineering and Management Systems Conference (APIEMS), 3-6 December 2013 Cebu, Philippines, page 1-6.
Topik: Distributed Flexible Job Shop; Scheduling; Genetic Algorithms; Solution Representation Scheme.
Fulltext: 3001.pdf (316.46KB)

Isi artikel

This research studies a distributed and flexible job shops scheduling problem (DFJSP). The DFJSP involves three sub-decisions: (1) job-to-cell assignment, (2) operation-to-machine assignment, (3) operation sequencing on a machine. To solve the DFJSP by meta-heuristic algorithms, we propose a new solution representation scheme (called Snew), which models the operations of all jobs to be scheduled by a sequence. Based on Snew, this research develops a genetic algorithm (called GA_Snew) to solve the DFJSP. Experiments indicate that GA_Snew outperform the state-of-the-art work (called GA_Sold), which is a genetic algorithm based on a traditional solution representation scheme.

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