In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. Artificial Ants stand for multiagent methods inspired by the behavior of real ants. This thesis investigates an ex ample of the latter, Bee Colony Optimization, on both an established optimization problem in the form of the Quadratic Assignment Problem and the FireFighting problem, which has not been studied before as an optimization problem.
Singh, A. (2009), An artificial bee colony algorithm for the leafconstrained minimum spanning tree problem, Applied Soft Computing, 9 (2),Elsevier, Netherlands. Tereshko, V.Loengarov, A. (2005), Collective decisionmaking in honey bee foraging dynamics, Computing and Information Systems, 9 (3): 17, University of the West of thesis using two efficient optimization methods, Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO).
A hybrid produced from these two algorithms is This thesis explores the application of Bee Colony Optimization (a swarm intelli generation to achieve software test optimization.
6. 4 PROPOSED ARTIFICIAL BEE COLONY BASED TEST SUITE OPTIMIZATION FRAMEWORK Need for Artificial Bee Colony (ABC) Based Approach As the outcome of the literature study on related work in software test suite optimization, the following observations were made. Visual and Infrared Patchwise DCT based Image Fusion using Artificial Bee Colony Optimization and Image Segmentation Thesis submitted in the View Bee Colony Optimization Research Papers on Academia. edu for free. Artificial Bee Colony (ABC) algorithm is one of the most recently introduced swarmbased algorithms.
ABC simulates the intelligent foraging behaviour of a honeybee swarm. Mar 13, 2009 In fact my Masters thesis investigated optimization using genetic algorithms which mimic evolutionary processes by simulating genetic crossover and mutation.
During the past few months Ive been looking at optimization algorithms which are based on the behavior of honey bee colonies.