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IJCNN
2006
IEEE

Job-Shop Scheduling with an Adaptive Neural Network and Local Search Hybrid Approach

10 years 4 months ago
Job-Shop Scheduling with an Adaptive Neural Network and Local Search Hybrid Approach
— Job-shop scheduling is one of the most difficult production scheduling problems in industry. This paper proposes an adaptive neural network and local search hybrid approach for the job-shop scheduling problem. The adaptive neural network is constructed based on constraint satisfactions of job-shop scheduling and can adapt its structure and neuron connections during the solving process. The neural network is used to solve feasible schedules for the job-shop scheduling problem while the local search scheme aims to improve the performance by searching the neighbourhood of a given feasible schedule. The experimental study validates the proposed hybrid approach for job-shop scheduling regarding the quality of solutions and the computing speed.
Shengxiang Yang
Added 11 Jun 2010
Updated 11 Jun 2010
Type Conference
Year 2006
Where IJCNN
Authors Shengxiang Yang
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