Application of the Artificial Bee Colony Based on Boltzmann in Geometric Constraint Problem

Content Provider	Semantic Scholar
Author	Li, Wenhui Sun, Mingyu
Copyright Year	2015
Abstract	Solving the geometric constraint problem is substantially equivalent to solving a system of nonlinear equations; furthermore, we can transform a geometric constraint problem to an optimization problem. By using Artificial Bee Colony, the optimization problem can be solved. The Artificial Bee Colony (ABC) algorithm is an optimization algorithm and mainly on the basis of the intelligent act of honeybees. In this paper, an improved ABC algorithm is proposed (also called BABC) based on the Boltzmann selection mechanism and used to solve the geometric constraint. BABC algorithm makes the initial group symmetrically. Instead of roulette, this method uses Boltzmann selection mechanism to avoid premature. Experiment results indicate that the BABC has effectively improved the solution efficiency of the geometric constraint problems and better converge to the optimal solution than the traditional ABC algorithms.
File Format	PDF HTM / HTML
Alternate Webpage(s)	https://pos.sissa.it/259/002/pdf
Language	English
Access Restriction	Open
Subject Keyword	Apis mellifera Approximation algorithm Artificial bee colony algorithm Bees Boltzmann machine Colony Collapse Disorder Constraint satisfaction problem Converge Evolutionary algorithm Genetic algorithm Local convergence Mathematical optimization Nonlinear system Optimization problem Parallel computing Parametric design Swarm intelligence
Content Type	Text
Resource Type	Article