NDLI: MBO: marriage in honey bees optimization-a Haplometrosis polygynous swarming approach

Content Provider	IEEE Xplore Digital Library
Author	Abbass, H.A.
Copyright Year	2001
Description	Author affiliation: Sch. of Comput. Sci., New South Wales Univ., Canberra, ACT, Australia (Abbass, H.A.)
Abstract	Honey-bees are one of the most well studied social insects. They exhibit many features that distinguish their use as models for intelligent behavior. These features include division of labor, communication on the individual and group level, and cooperative behavior. In this paper, we present a unified model for the marriage in honey-bees within an optimization context. The model simulates the evolution of honey-bees starting with a solitary colony (single queen without a family) to the emergence of an eusocial colony (one or more queens with a family). From optimization point of view, the model is a committee machine approach where we evolve solutions using a committee of heuristics. The model is applied to a fifty propositional satisfiability problems (SAT) with 50 variables and 215 constraints to guarantee that the problems are centered on the phase transition of 3-SAT. Our aim in this paper is to analyze the behavior of the algorithm using biological concepts (number of queens, spermatheca size, and number of broods) rather than trying to improve the performance of the algorithm while losing the underlying biological essence. Notwithstanding, the algorithm outperformed WalkSAT, one of the state-of-the-art algorithms for SAT.
Starting Page	207
Ending Page	214
File Size	744005
Page Count	8
File Format	PDF
ISBN	0780366573
DOI	10.1109/CEC.2001.934391
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-05-27
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Insects Biological system modeling Ant colony optimization Computer science Educational institutions Drives Australia Context modeling Evolution (biology) Performance analysis
Content Type	Text
Resource Type	Article

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