A Meta-Heuristic with Ant Colony Approach to Complex System

Zong Li Liu; Jie Cao; Zhan Ting Yuan

doi:10.4028/www.scientific.net/AMM.26-28.1147

Paper Titles

Investigation of Belt Conveyor Transfer Chute Configurations to Reduce Dust Generation Using CFD Modeling
p.1126

Experimental Study of Green High-Speed Turning Nickel-Based Superalloy GH4169
p.1132

Time-Dependent Temperature Distribution of Sheets in the Stage of Storing
p.1137

Production of Zinc Powder by Alkaline Hydrometallurgy
p.1142

A Meta-Heuristic with Ant Colony Approach to Complex System
p.1147

A Hybrid Swarm Optimization Algorithm for Complex Assignment Problem
p.1151

A Hybrid Algorithm Based on PSO and DE and Its Application in Complexity System
p.1155

A Dynamic Re-Configuration and Order Optimization Model and Optimization Algorithm in Complex System
p.1159

Infrared Image Multi-Scale Recognition Based on Gabor Wavelet
p.1163

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 26-28A Meta-Heuristic with Ant Colony Approach to...

A Meta-Heuristic with Ant Colony Approach to Complex System

Abstract:

This paper proposes a new approach to determining the complex system design for a product mix comprising complex hierarchies of subassembly and components. Pareto Ant Colony Optimisation as an especially effective meta-heuristic for solving the problem of complex system design was introduced in this paper. A Pareto Optimal Set of complex system in which only the non dominated solutions allow ants to deposit pheromones over the time and cost pheromone matrices after certain generation runs. Simulation results show that the model for complex system and the hybrid algorithms are effective to the design of complex system.