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AMC
2005
191views more  AMC 2005»
13 years 7 months ago
Model identification of ARIMA family using genetic algorithms
ARIMA is a popular method to analyze stationary univariate time series data. There are usually three main stages to build an ARIMA model, including model identification, model est...
Chorng-Shyong Ong, Jih-Jeng Huang, Gwo-Hshiung Tze...
CEC
2007
IEEE
14 years 1 months ago
SAT-decoding in evolutionary algorithms for discrete constrained optimization problems
— For complex optimization problems, several population-based heuristics like Multi-Objective Evolutionary Algorithms have been developed. These algorithms are aiming to deliver ...
Martin Lukasiewycz, Michael Glaß, Christian ...
COR
2010
155views more  COR 2010»
13 years 7 months ago
A memetic algorithm for the multi-compartment vehicle routing problem with stochastic demands
The Multi-Compartment Vehicle Routing Problem (MC-VRP) consists of designing transportation routes to satisfy the demands of a set of costumers for several products that because o...
Jorge E. Mendoza, Bruno Castanier, Christelle Gu&e...
GECCO
2000
Springer
156views Optimization» more  GECCO 2000»
13 years 11 months ago
Optimal Mutation Rates and Selection Pressure in Genetic Algorithms
It has been argued that optimal per-locus mutation rates in GAs are proportional to selection pressure and the reciprocal of genotype length. In this paper we suggest that the not...
Gabriela Ochoa, Inman Harvey, Hilary Buxton
ADVAI
2010
110views more  ADVAI 2010»
13 years 1 months ago
Using Genetic Algorithms to Represent Higher-Level Planning in Simulation Models of Conflict
The focus of warfare has shifted from the Industrial Age to the Information Age, as encapsulated by the term Network Enabled Capability. This emphasises information sharing, comma...
James Moffat, Susan Fellows