Biologically inspired algorithims for job shop scheduling optimization
This project aims to explore and develop new biologically inspired algorithms for optimizing job shop scheduling problems. This project was motivated by the work carried out by Nakrani and Tovey (2004), on using a honey bee algorithm for dynamic allocation of Internet servers. In their algorithm, se...
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sg-ntu-dr.10356-423422023-03-03T20:22:01Z Biologically inspired algorithims for job shop scheduling optimization Low, Malcolm Yoke Hean. School of Computer Engineering DRNTU::Engineering::Manufacturing::Production management This project aims to explore and develop new biologically inspired algorithms for optimizing job shop scheduling problems. This project was motivated by the work carried out by Nakrani and Tovey (2004), on using a honey bee algorithm for dynamic allocation of Internet servers. In their algorithm, servers and HTTP request queues in an Internet server colony are modelled as foraging bees and flower patches respectively. In this project, we have successfully developed several bee colony optimization algorithms for the job shop scheduling, and have also extended the algorithms to other problem domains such as the travelling salesman problems as well as multi-objective simulation-based optimization for defence decision making process. The results of the finding from the project have been published in international journal and conferences. The work from the project has also led to the establishment of other research collaboration projects with external institutions in the domain of manufacturing, maritime as well as defence. SUG 10/07 2010-11-03T06:36:50Z 2010-11-03T06:36:50Z 2009 2009 Research Report http://hdl.handle.net/10356/42342 en 19 p. application/pdf |
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DRNTU::Engineering::Manufacturing::Production management Low, Malcolm Yoke Hean. Biologically inspired algorithims for job shop scheduling optimization |
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This project aims to explore and develop new biologically inspired algorithms for optimizing job shop scheduling problems. This project was motivated by the work carried out by Nakrani and Tovey (2004), on using a honey bee algorithm for dynamic allocation of Internet servers. In their algorithm, servers and HTTP request queues in an Internet server colony are modelled as foraging bees and flower patches respectively. In this project, we have successfully developed several bee colony optimization algorithms for the job shop scheduling, and have also extended the algorithms to other problem domains such as the travelling salesman problems as well as multi-objective simulation-based optimization for defence decision making process. The results of the finding from the project have been published in international journal and conferences. The work from the project has also led to the establishment of other research collaboration projects with external institutions in the domain of manufacturing, maritime as well as defence. |
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School of Computer Engineering |
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School of Computer Engineering Low, Malcolm Yoke Hean. |
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Research Report |
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Low, Malcolm Yoke Hean. |
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Low, Malcolm Yoke Hean. |
title |
Biologically inspired algorithims for job shop scheduling optimization |
title_short |
Biologically inspired algorithims for job shop scheduling optimization |
title_full |
Biologically inspired algorithims for job shop scheduling optimization |
title_fullStr |
Biologically inspired algorithims for job shop scheduling optimization |
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Biologically inspired algorithims for job shop scheduling optimization |
title_sort |
biologically inspired algorithims for job shop scheduling optimization |
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2010 |
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http://hdl.handle.net/10356/42342 |
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