Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/42342
Title: Biologically inspired algorithims for job shop scheduling optimization
Authors: Low, Malcolm Yoke Hean.
Keywords: DRNTU::Engineering::Manufacturing::Production management
Issue Date: 2009
Abstract: 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.
URI: http://hdl.handle.net/10356/42342
Schools: School of Computer Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Research Reports (Staff & Graduate Students)

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