The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using coo...
In this paper simulation studies of the ultrasound computerized tomography (CT) technique employing time of flight data is presented. An enhanced genetic algorithm based reconstru...
Shyam P. Kodali, Sunith Bandaru, Kalyanmoy Deb, Pr...
This paper introduces GLOCSA as a new scoring function to rate multiple sequence alignments. It is intended to be simple, considering the whole alignment at once and reflecting t...
The landscape formalism unites a finite candidate solution set to a neighborhood topology and an objective function. This construct can be used to model the behavior of local sea...
A new evolutionary method named “Genetic Network Programming with Control Nodes, GNPcn” has been proposed and applied to determine the timing of buying and selling stocks. GNP...
Etsushi Ohkawa, Yan Chen, Shingo Mabu, Kaoru Shima...
One problem that has plagued Genetic Programming (GP) and its derivatives is numerical constant creation. Given a mathematical formula expressed as a tree structure, the leaf node...
Our previous work has introduced a hyperheuristic (HH) approach based on Genetic Programming (GP). There, GP employs usergiven languages where domain-specific local heuristics ar...
In Multi-Objective Problems (MOPs) involving uncertainty, each solution might be associated with a cluster of performances in the objective space depending on the possible scenari...
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
Genetic-Based Machine Learning Systems (GBML) are comparable in accuracy with other learning methods. However, efficiency is a significant drawback. This paper presents a new rep...