| Description |
1 online resource |
| Series |
Springer theses, 2190-5061 |
|
Springer theses. 2190-5061
|
| Summary |
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 |
| Notes |
"Doctoral thesis accepted by University of South Australia, Adelaide, Australia." |
| Bibliography |
Includes bibliographical references |
| Notes |
Online resource; title from PDF title page (EBSCO, viewed January 11, 2018) |
| Subject |
Production scheduling -- Data processing
|
|
Artificial intelligence.
|
|
Production engineering.
|
|
Management of specific areas.
|
|
Engineering: general.
|
|
BUSINESS & ECONOMICS -- Industrial Management.
|
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BUSINESS & ECONOMICS -- Management.
|
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BUSINESS & ECONOMICS -- Management Science.
|
|
BUSINESS & ECONOMICS -- Organizational Behavior.
|
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Production scheduling -- Data processing
|
| Form |
Electronic book
|
| ISBN |
9783319721132 |
|
3319721135 |
|
