NDLI: A two-stage no-wait job shop scheduling problem by using a neuro-evolutionary variable neighborhood search

Content Provider	Springer Nature Link
Author	Mokhtari, Hadi
Copyright Year	2014
Abstract	A two-stage order scheduling problem with an additional no-wait condition is studied in this article. All orders must be processed from start to completion without any waiting between operations and any interruption within operations. Examples of such a problem occur in steel production and pharmaceutical, chemical, and construction industries. A new optimization method which is based on a combination of an enhanced variable neighborhood search (VNS) and an artificial neural network (ANN) is devised in this paper. The aim is to simultaneously employ the key characteristics of two approaches to achieve superior solutions in solving the addressed optimization problem. In proposed algorithm, the VNS performs a global search whereas the ANN plays the role of intensive initial solution. The individual obtained by feed forward back-propagation ANN is improved within enhanced VNS iterations. The two techniques complement each other when ANN feeds its best solution to the VNS algorithm. Furthermore, to establish the best sequence of order pairs, a team process algorithm is also embedded into the VNS to enhance the search diversification as well as its intensification. The performance of proposed neuro-evolutionary algorithm is investigated via computational experiments, and the results prove the appropriate performance of suggested VNS-ANN algorithm.
Starting Page	1595
Ending Page	1610
Page Count	16
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	74
Issue Number	9-12
e-ISSN	14333015
Language	English
Publisher	Springer London
Publisher Date	2014-07-05
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Order scheduling Artificial neural network Variable neighborhood search Neuro-evolutionary Industrial and Production Engineering Production/Logistics/Supply Chain Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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