System Development of a Simulated Annealing Algorithm for Job-Shop Scheduling Problem Based on Delphi

Yan Cao; Sen Cao; Lei Lei; Yu Bai; Lei Shi

doi:10.4028/www.scientific.net/AMR.411.411

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Order Parameters Evaluation Indexes and Quantitative Analysis Model on Order Degree of Manufacturing System
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Application of Ant Colony Algorithm to Job-Shop Scheduling Problem
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System Development of a Simulated Annealing Algorithm for Job-Shop Scheduling Problem Based on Delphi
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Review of Fabrication Methods of Nanotube / Nanowire Devices
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Mechanism and Effect of Charges Accumulation on Differential Capacitance Detector Diodes in MEMS Accelerometer
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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 411System Development of a Simulated Annealing...

System Development of a Simulated Annealing Algorithm for Job-Shop Scheduling Problem Based on Delphi

Abstract:

The job-shop scheduling is the key element of a manufacturing execution system (MES). It is significant for enterprises to utilize resources rationally, enhance product quality, shorten production cycle, reduce production cost, and improve its market competitiveness. In the paper, Simulated Annealing (SA) algorithm is adopted to solve the job-shop scheduling problem. SA algorithm is a random search method proposed to solve large-scale combinatorial optimization problems. As an efficient and general method, the optimization and convergence performance of SA algorithm is mainly affected by the problem and several factors. In order to facilitate use’s employment, a job-shop scheduling system based on SA algorithm is developed using Delphi. The system developed is verified by an example. The results show that it is an effective solution to the job-shop scheduling problems.

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Periodical:

Advanced Materials Research (Volume 411)

Pages:

411-414

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.411.411

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Online since:

November 2011

Authors:

Yan Cao, Sen Cao, Lei Lei, Yu Bai, Lei Shi

Keywords:

Combinatorial Optimization, Delphi, Development, Job Shop Scheduling, Simulated Annealing Algorithm

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