Nature-Inspired Intelligent Optimisation Using the Bees Algorithm

Pham, Duc Truong; Castellani, Marco; Thi, Hoai An Le

doi:10.1007/978-3-642-54455-2_2

Cited by 19 publications

(10 citation statements)

References 66 publications

(75 reference statements)

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“…Solomon (1987) The time windows constraint that should not be violated is presented as follow: BA firstly proposed by Pham et al (2005). BA has been applied in various optimisation fields (Pham et al 2006(Pham et al , 2006a(Pham et al , 2006b(Pham et al , 2007Pham & Castellani, 2009). BA consists of two groups of bees, i.e.…”

Section: Vehicle Routing Problems With Time Windows (Vrptw)mentioning

confidence: 99%

Bee Algorithm for the vehicle routing problems with time windows

Alzaqebah¹,

Abdullah²,

Jawarneh³

2016

Fifth International Conference on Advances in Computing, Control and Networking - ACCN 2016

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Abstract-The natural honeybee's behavior has been modelled by researchers to solve optimization problems. This paper introduces the Bee algorithm based on honeybee behavior for the vehicle routing problem with time windows (VRPTW). The algorithm has been tested on Solomon instances. The encoding of the problem and the operations needed to implement algorithm are outlined. Experiments show that on the considered instances, using BA performs almost as well as planning for long-term, while using much less computation time. Overall, computational investigations show that the proposed algorithm is good and promising approach for the VRPTW.Keywords-Foraging behaviour; bee algorithm; vehicle routing problem with time windows.

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Section: Vehicle Routing Problems With Time Windows (Vrptw)mentioning

confidence: 99%

Bee Algorithm for the vehicle routing problems with time windows

Alzaqebah¹,

Abdullah²,

Jawarneh³

2016

Fifth International Conference on Advances in Computing, Control and Networking - ACCN 2016

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“…They then carry out localized and organized searches until they find the most efficient possible location for food recovery process. The algorithm can be used for both combinatorial optimization [16,17] and functional optimization [18]. Figure 1 illustrates the pseudocode for a simple BA.…”

Section: Bees Algorithm (Ba)mentioning

confidence: 99%

A new feature selection model based on ID3 and bees algorithm for intrusion detection system

Eesa¹,

Orman²,

Brifcani³

2015

Turk J Elec Eng & Comp Sci

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Abstract:Intrusion detection systems (IDSs) have become a necessary component of computers and information security framework. IDSs commonly deal with a large amount of data traffic and these data may contain redundant and unimportant features. Choosing the best quality of features that represent all of the data and exclude the redundant features is a crucial topic in IDSs. In this paper, a new combination approach based on the ID3 algorithm and the bees algorithm (BA) is proposed to select the optimal subset of features for an IDS. The BA is used to generate a subset of features, and the ID3 algorithm is used as a classifier. The proposed model is applied on KDD Cup 99 dataset. The obtained results show that the feature subset generated by the proposed ID3-BA gives a higher accuracy and detection rate with a lower false alarm rate when compared to the results obtained by using all features.

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“…The queen bee has only an indirect role in organizing the colony, she gives birth to bees. The self-organizing model of honey bees has inspired much work in computer science and shown to improve considerably computational performance in particular circumstances [3], [4], [5].…”

Section: Overviewmentioning

confidence: 99%

“…When the address is found, RegionMaster returns it to the requesting party (7); if not, RegionMaster broadcasts a query to all RegionMasters of the global system (4). Each RegionMaster of the global network checks its cache for the address (5). Whenever the address is found by one of the RegionMasters, it will be sent back to the requesting RegionMaster (6).…”

Section: Managing Mobile Agent's Locationmentioning

confidence: 99%

Mobile Agent Communication in Highly Dynamic Networks: A Self-Adaptive Architecture inspired by the Honey Bee Colony

Nguyen

Schau²,

Rossak³

2014

EAI Endorsed Transactions on Context-aware Systems and Applicat

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Communication is considered as a building block for mobile agent systems. In highly dynamic networks, thanks to environmental stimuli such as changes in connection quality and network topology, performance of communication between mobile agents may be degraded considerably. With focus on attaining fault tolerance and reliability, we propose a context-aware architecture for agent communication model inspired by the honey bee colony. To validate the hypothesis, a software prototype has been designed and implemented according to the proposed mechanism. Encouraging experimental results on a test system show that our approach brings benefits to a colony of agent platforms.

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Nature-Inspired Intelligent Optimisation Using the Bees Algorithm

Cited by 19 publications

References 66 publications

Bee Algorithm for the vehicle routing problems with time windows

Bee Algorithm for the vehicle routing problems with time windows

A new feature selection model based on ID3 and bees algorithm for intrusion detection system

Mobile Agent Communication in Highly Dynamic Networks: A Self-Adaptive Architecture inspired by the Honey Bee Colony

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