Paper Info
Title
Population-based optimization having deterministic and discrete dynamics
Abstract
In this paper, we propose a method celled Integer algorithm of Population-based Optimization based on Piecewise Constant Oscillator (IPO-PCO). Well known Particle Swarm Optimization method (PSO) has several open problems. We focus on two of them. First, in order to solve discrete optimization problems, PSO needs some modifications. Second, since PSO has stochastic factors in the dynamics, the analysis of the dynamic behavior is pretty complex. Some means to resolve the problems have been proposed in previous works. However there is no method which can manage both problems. Then, this paper considers a deterministic and discrete method. We compare the proposed method with a discretized PSO by repositioned to near lattice point and verify the effectiveness of the propose method.
Year
DOI
Venue
2015
10.1109/CEC.2015.7257216
Evolutionary Computation
Keywords
Field
DocType
integer programming,lattice theory,particle swarm optimisation,stochastic programming,IPO-PCO,PSO,deterministic dynamics,discrete dynamics,discrete optimization problems,dynamic behavior analysis,integer algorithm,near lattice point,particle swarm optimization method,piecewise constant oscillator,population-based optimization,stochastic factors
Continuous optimization,Mathematical optimization,Stochastic optimization,Computer science,Discrete optimization,Multi-swarm optimization,Stochastic programming,Optimization problem,Imperialist competitive algorithm,Metaheuristic
Conference
Citations 
PageRank 
References 
0
0.34
4
Authors
2
Name
Order
Citations
PageRank
Yuya Kurita100.68
Tadashi Tsubone2209.43