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Modelling and Intelligent Optimisati...
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Modelling and Intelligent Optimisation of Production Scheduling in VCIM Systems
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Modelling and Intelligent Optimisation of Production Scheduling in VCIM Systems/ by Son Duy Dao.
Author:
Dao, Son Duy.
Description:
XVII, 147 p. 17 illus., 11 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Engineering economics. -
Online resource:
https://doi.org/10.1007/978-3-319-72113-2
ISBN:
9783319721132
Modelling and Intelligent Optimisation of Production Scheduling in VCIM Systems
Dao, Son Duy.
Modelling and Intelligent Optimisation of Production Scheduling in VCIM Systems
[electronic resource] /by Son Duy Dao. - 1st ed. 2018. - XVII, 147 p. 17 illus., 11 illus. in color.online resource. - Springer Theses, Recognizing Outstanding Ph.D. Research,2190-5053. - Springer Theses, Recognizing Outstanding Ph.D. Research,.
This thesis reports on an innovative production-scheduling model for virtual computer-integrated manufacturing (VCIM) systems. It also describes a robust genetic algorithm for production scheduling in VCIM systems. The model, which is the most comprehensive of its kind to date, is not only capable of supporting collaborative shipment scheduling and handling multiple product orders simultaneously, but also helps cope with multiple objective functions under uncertainties. In turn, the genetic algorithm, characterised by an innovative algorithm structure, chromosome encoding, crossover and mutation, is capable of searching for optimal/suboptimal solutions to the complex optimisation problem in the VCIM production- scheduling model described. Lastly, the effectiveness of the proposed approach is verified in a comprehensive case study.
ISBN: 9783319721132
Standard No.: 10.1007/978-3-319-72113-2doiSubjects--Topical Terms:
1253802
Engineering economics.
LC Class. No.: TA177.4-185
Dewey Class. No.: 658.5
Modelling and Intelligent Optimisation of Production Scheduling in VCIM Systems
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This thesis reports on an innovative production-scheduling model for virtual computer-integrated manufacturing (VCIM) systems. It also describes a robust genetic algorithm for production scheduling in VCIM systems. The model, which is the most comprehensive of its kind to date, is not only capable of supporting collaborative shipment scheduling and handling multiple product orders simultaneously, but also helps cope with multiple objective functions under uncertainties. In turn, the genetic algorithm, characterised by an innovative algorithm structure, chromosome encoding, crossover and mutation, is capable of searching for optimal/suboptimal solutions to the complex optimisation problem in the VCIM production- scheduling model described. Lastly, the effectiveness of the proposed approach is verified in a comprehensive case study.
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