Multi-Objective Artificial Glowworm Swarm Optimization Algorithm And Application

Artificial Glowworm Swarm Optimization Algorithm is a new swarm intelligence technique to simulate the behavior of a group of glowworms which aim to find food and seek spouses. GSO has some attractive characteristics, such as looking for extremely domain quickly and high efficiency, simple in principle, easily implemented, versatility and so on. However, at the same time the algorithm is poor in precision of problem, easy to fall into local optimal solution, has slow convergence speed and concussion. According to the shortcoming of GSO and the characteristics of multi-objective optimization, this paper puts forward some new mechanism and strategies and improvers the artificial glowworm swarm optimization algorithm. The improved artificial glowworm swarm optimization algorithm is used to solve knapsack problem and multi-objective optimization problems. The main results of this research are as follows:(1) According to the problem of conventional solving knapsack problem penalty function method sensitive parameters selection, this paper uses artificial glowworm swarm optimization algorithm to solve knapsack problem.(2) Research on how to combine precise optimization method - greedy algorithm and artificial fireflies swarm optimization algorithm. The algorithm utilizes two important strategies, how to select the item based on its average value and the binary glowworm swarm optimization algorithm and used to solving multi-dimensional knapsack problem.(3) A multi-objective artificially glowworm swarm optimization algorithm based on Pareto optima set is brought forward In this paper, by adopting a container called"Pareto Library"to store Pareto optima found, Glowworms in "Pareto Library"must be made comparisons each other and eliminated gradually, at last a whole Pareto optima set would be achieved.(4) The method that is based on penalty function is made use of converting constrainted optimization problems and make good use of multi-objective artificial glowworm swarm optimization algorithm to solve constrained optimization problems and multi-objective programming problem.