A modified Pareto strength ant colony optimization algorithm for the multi-objective optimization problems

2016 ◽  
Author(s):  
I.D.I.D. Ariyasingha ◽  
T.G.I. Fernando
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Optimization Problems ◽  
Ant Colony ◽  
Multi Objective Optimization ◽  
Ant Colony Optimization Algorithm ◽  
Multi Objective

Convergence Speed of Multi-Objective Generalized Ant Colony Optimization Algorithm

2014 ◽  
Vol 989-994 ◽  
pp. 1732-1735
Author(s):  
Dai Yuan Zhang ◽  
Peng Fu
Keyword(s):  
Markov Chain ◽  
Ant Colony Optimization ◽  
Optimization Problems ◽  
Convergence Speed ◽  
Ant Colony ◽  
Multi Objective Optimization ◽  
Ant Colony Optimization Algorithm ◽  
Multi Objective ◽  
Absorbing State ◽  
Simulation Results

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.

ANT COLONY OPTIMIZATION ALGORITHM FOR HETEROGENEOUS REDUNDANCY ALLOCATION IN MULTI-STATE SERIES-PARALLEL SYSTEMS

2009 ◽  
Vol 16 (02) ◽  
pp. 163-186 ◽  
Author(s):  
MANJU AGARWAL ◽  
VIKAS K. SHARMA
Keyword(s):  
System Design ◽  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
System Reliability ◽  
Optimization Problems ◽  
Ant Colony ◽  
System Structure ◽  
Ant Colony Optimization Algorithm ◽  
Redundancy Allocation ◽  
Demand Distribution

This paper addresses the redundancy allocation problem of multi-state series-parallel reliability structures where each subsystem can consist of maximum two types of redundant components. The objective is to minimize the total investment cost of system design satisfying system reliability constraint and the consumer load demand. The demand distribution is presented as a piecewise cumulative load curve. The configuration uses the binary components from a list of available products to provide redundancy so as to increase system reliability. The components are characterized by their feeding capacity, reliability and cost. A system that consists of elements with different reliability and productivity parameters has the capacity strongly dependent upon the selection of components constituting its structure. An ant colony optimization algorithm has been presented to analyze the problem and suggest an optimal system structure. The solution approach consists of a series of simple steps as used in early ant colony optimization algorithms dealing with other optimization problems and still proves efficient over the prevalent methods with regard to solutions obtained/computation time. Three multi-state system design problems have been solved for illustration.

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