A new adaptive neural network and heuristics hybrid approach for job-shop scheduling
Computers & Operations ResearchPublished 1 September 2001
Shengxiang Yang, Dingwei Wang
Citations66
SJR quartileQ1
SJR score1.60
SNIP2.02
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TL;DR
A new adaptive neural network and heuristics hybrid approach for job-shop scheduling is presented, which is of high speed and efficiency and can be combined with the neural network.
Abstract
A new adaptive neural network and heuristics hybrid approach for job-shop scheduling is presented. The neural network has the property of adapting its connection weights and biases of neural units while solving the feasible solution. Two heuristics are presented, which can be combined with the neural network. One heuristic is used to accelerate the solving process of the neural network and guarantee its convergence, the other heuristic is used to obtain non-delay schedules from the feasible solutions gained by the neural network. Computer simulations have shown that the proposed hybrid approach is of high speed and efficiency. The strategy for solving practical job-shop scheduling problems is provided.
Keywords
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