DocumentCode :
3252224
Title :
MBO: marriage in honey bees optimization-a Haplometrosis polygynous swarming approach
Author :
Abbass, Hussein A.
Author_Institution :
Sch. of Comput. Sci., New South Wales Univ., Canberra, ACT, Australia
Volume :
1
fYear :
2001
fDate :
2001
Firstpage :
207
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
Keywords :
computability; optimisation; Haplometrosis polygynous swarming approach; MBO; WalkSAT; committee machine approach; cooperative behavior; eusocial colony; group level; intelligent behavior; marriage in honey bees optimization; propositional satisfiability problems; social insects; solitary colony; unified model; Ant colony optimization; Australia; Biological system modeling; Computer science; Context modeling; Drives; Educational institutions; Evolution (biology); Insects; Performance analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2001. Proceedings of the 2001 Congress on
Conference_Location :
Seoul
Print_ISBN :
0-7803-6657-3
Type :
conf
DOI :
10.1109/CEC.2001.934391
Filename :
934391
Link To Document :
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