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Applying neural network to job-shop scheduling problem | |
Author | Trinh Vu Minh |
Call Number | AIT Thesis no.ISE-03-42 |
Subject(s) | Neural networks (Computer science) Production scheduling |
Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Advanced Technologies |
Publisher | Asian Institute of Technology |
Series Statement | Thesis ; no. ISE-03-42 |
Abstract | The objective of this study is to development an algorithm to solve the job-shop scheduling problem. In the job-shop scheduling problem, a set of n jobs that have to be processed on m machines. Each job is composed of a set of operations that have to be processed in a predefined order. The problem is to find the best sequence of operations on each machine in order to minimize the maximum completed time or any other regular performance measure without violating sequence and resource constraints. In this study, two heuristics for job-shop scheduling problem will be presented. The first algorithm is a hybrid neural network model approach, which was developed from Constraint Satisfaction Adaptive Neural Network (CSANN) model. And the second one is a new operations order exchange algorithm developed from local search algorithm. The algorithms were implemented and tested on various benchmark problems to evaluate the performance. The result shown that the first algorithm is a low performance algorithm in both speed and accuracy. The second algorithm can find local optimum value quickly and return good result for most of the testing problems. |
Year | 2003 |
Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. ISE-03-42 |
Type | Thesis |
School | School of Advanced Technologies (SAT) |
Department | Department of Industrial Systems Engineering (DISE) |
Academic Program/FoS | Industrial Systems Engineering (ISE) |
Chairperson(s) | Voratas Kachitvichyanukul; |
Examination Committee(s) | Afzulpurkar, Nitin V.;Manukid Parnichkun; |
Scholarship Donor(s) | Ministry of Education and Training; |
Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2003 |