A generic bee colony optimization framework for combinatorial optimization problems

Combinatorial optimization is one of the areas that has been studied intensively in computer science and operations research. Solving a Combinatorial Optimization Problem (COP) is NP-hard [55] and it involves finding a set of feasible solutions with the least-cost in a discrete search space [90]. It...

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Main Author: Wong, Li Pei
Other Authors: He Bingsheng
Format: Theses and Dissertations
Language:English
Published: 2012
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Online Access:https://hdl.handle.net/10356/48091
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-480912023-03-04T00:40:54Z A generic bee colony optimization framework for combinatorial optimization problems Wong, Li Pei He Bingsheng Chong Chin Soon Low Yoke Hean, Malcolm School of Computer Engineering Parallel and Distributed Computing Centre DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Combinatorial optimization is one of the areas that has been studied intensively in computer science and operations research. Solving a Combinatorial Optimization Problem (COP) is NP-hard [55] and it involves finding a set of feasible solutions with the least-cost in a discrete search space [90]. It becomes complicated when the COP being solved is with large scale data, constraints and variables. The significance of COPs can be found in various types of industrial applications. Examples include finding an optimized scan chains route in integrated chips testing and job scheduling in manufacturing industries. This thesis presents a generic Bee Colony Optimization (BCO) framework for solving different COPs. The framework realizes computationally the collective intelligence shown in bee foraging behaviour. In a bee colony, bees are sent out of their beehive and travel across different locations to discover and to collect food. When a bee found a food source, it would perform waggle dance upon flying back to its hive. Its intension is to recruit more bees towards the newly discovered food source. Waggle dance operates as an important communication tool among bees. This collective intelligence shown in the bee foraging behaviour is modelled algorithmically as a generic framework to solve different COPs. The generic BCO framework is designed using the object-oriented approach. A set of domain independent and abstract classes are defined. The domain independent classes implement the bee foraging behaviour and the abstract classes act as an interface to interact with domain specific classes. To solve a COP with the proposed framework, the implementation of domain specific tasks as defined in the abstract classes needs to be supplied to the framework. Besides the advantage of solving different COPs, the proposed BCO framework can be modified or enhanced flexibly and the effect of the enhancement will be applicable across all different COPs being solved. DOCTOR OF PHILOSOPHY (SCE) 2012-03-16T00:59:10Z 2012-03-16T00:59:10Z 2012 2012 Thesis Wong, L. P. (2012). A generic bee colony optimization framework for combinatorial optimization problems. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/48091 10.32657/10356/48091 en 203 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Wong, Li Pei
A generic bee colony optimization framework for combinatorial optimization problems
description Combinatorial optimization is one of the areas that has been studied intensively in computer science and operations research. Solving a Combinatorial Optimization Problem (COP) is NP-hard [55] and it involves finding a set of feasible solutions with the least-cost in a discrete search space [90]. It becomes complicated when the COP being solved is with large scale data, constraints and variables. The significance of COPs can be found in various types of industrial applications. Examples include finding an optimized scan chains route in integrated chips testing and job scheduling in manufacturing industries. This thesis presents a generic Bee Colony Optimization (BCO) framework for solving different COPs. The framework realizes computationally the collective intelligence shown in bee foraging behaviour. In a bee colony, bees are sent out of their beehive and travel across different locations to discover and to collect food. When a bee found a food source, it would perform waggle dance upon flying back to its hive. Its intension is to recruit more bees towards the newly discovered food source. Waggle dance operates as an important communication tool among bees. This collective intelligence shown in the bee foraging behaviour is modelled algorithmically as a generic framework to solve different COPs. The generic BCO framework is designed using the object-oriented approach. A set of domain independent and abstract classes are defined. The domain independent classes implement the bee foraging behaviour and the abstract classes act as an interface to interact with domain specific classes. To solve a COP with the proposed framework, the implementation of domain specific tasks as defined in the abstract classes needs to be supplied to the framework. Besides the advantage of solving different COPs, the proposed BCO framework can be modified or enhanced flexibly and the effect of the enhancement will be applicable across all different COPs being solved.
author2 He Bingsheng
author_facet He Bingsheng
Wong, Li Pei
format Theses and Dissertations
author Wong, Li Pei
author_sort Wong, Li Pei
title A generic bee colony optimization framework for combinatorial optimization problems
title_short A generic bee colony optimization framework for combinatorial optimization problems
title_full A generic bee colony optimization framework for combinatorial optimization problems
title_fullStr A generic bee colony optimization framework for combinatorial optimization problems
title_full_unstemmed A generic bee colony optimization framework for combinatorial optimization problems
title_sort generic bee colony optimization framework for combinatorial optimization problems
publishDate 2012
url https://hdl.handle.net/10356/48091
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