Convergence Speed of Multi-Objective Generalized Ant Colony Optimization Algorithm

Abstract:

Multi-objective optimization problems are very important, but it is hard to optimized or solved. Generalized ant colony optimization (GACO) algorithm is a new kind of ant colony optimization (ACO) algorithm developed in recent years. In this paper, we try to combine Multi-objective optimization problems with GACO algorithm, established a model for multi-objective GACO algorithm by absorbing state Markov chain, and present a method for estimating the convergence speed of multi-objective GACO algorithm. Simulation results show that the convergence speed of multi-objective GACO algorithm is faster than traditional multi-objective ACO algorithm.

• Periodical: Advanced Materials Research (Volumes 989-994)
• Pages: 1732-1735
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.989-994.1732
• Online since: July 2014
• Authors: Dai Yuan Zhang*, Peng Fu
• Keywords: Convergence Speed, Generalized Ant Colony Algorithm, Multi-Objective

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