A new adaptive neural network and heuristics hybrid approach for job-shop scheduling

Date

2001-08-09

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

Elsevier

Type

Article

Peer reviewed

Yes

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.

Description

Keywords

Job-shop scheduling, Adaptive neural network, Heuristics

Citation

Yang, S. and Wang, D. (2001) A new adaptive neural network and heuristics hybrid approach for job-shop scheduling. Computers and Operations Research, 28 (10), pp. 955-971

Rights

Research Institute

Institute of Artificial Intelligence (IAI)