Job-shop scheduling optimization by parallel computing  

Oleh:

Tsai, Nai-Ling ; Liao, Kang-Yen ; Chen, Wu-Lin ; Lai, Yi-Chiuan ; Huang, Chin-Yin

Jenis: Article from Proceeding
Dalam koleksi: The 14th Asia Pacific Industrial Engineering and Management Systems Conference (APIEMS), 3-6 December 2013 Cebu, Philippines, page 1-10.
Topik: Mathematical Models ; Optimization/Artificial Intelligence Techniques ; Scheduling & Sequencing ; Parallel Computing
Fulltext: 3005.pdf (488.29KB)

Isi artikel

Scheduling is a key issue in resource utilization. However, optimization of a scheduling problem is an NP-hard problem. Hence, instead of applying mathematical programming to find the optimal schedules, most research takes heuristic algorithms and soft computing, et al. as tools to find the non-guaranteed optimal schedule. In order to maintain the optimization characteristics of mathematical programming and release NP-hard problem in finding the optimal schedule, this research introduces parallel computing in solving the problem. By taking the mathematical model of Flexible Job-shop Scheduling Problem with Process Plan Flexibility (FJSP-PPF) proposed by Ozguven et al. [1] as a basis, this research parallelizing the problem in a computer network with Java Remote Message Invocation. The results indicate that the schedule can be found in a reasonable time and the minimal makespan is guaranteed and the computation time reduces as the increase of the number of CPUs.

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