Multi-Objective Genetic Algorithm Using Class-Based Elitist Approach

A Fast Elitist Multi-Objective Genetic Algorithm: NSGA-II

MULTI-OBJECTIVE OPTIMIZATION OF TIME-COST-SAFETY USING GENETIC ALGORITHM

Safety risk management has a considerable effect on disproportionate injury rate of construction industry, project cost and both labor and public morale. On the other hand time-cost optimization (TCO) may earn a big profit for project stakeholders. This paper has addressed these issues to present a multi-objective optimization model to simultaneously optimize total time, total cost and overall ...

A Multi-Objective Approach to Fuzzy Clustering using ITLBO Algorithm

Data clustering is one of the most important areas of research in data mining and knowledge discovery. Recent research in this area has shown that the best clustering results can be achieved using multi-objective methods. In other words, assuming more than one criterion as objective functions for clustering data can measurably increase the quality of clustering. In this study, a model with two ...

A Novel Approach to Image Clustering using Elitist Genetic Algorithm

Genetic Algorithm (GA) is a stochastic randomized blind search and optimization technique based on evolutionary computing that has already been proved to be robust and effective from its outcome in solving problems from variety of application domains. Clustering is a vital technique to extract meaningful and hidden information from the datasets. Clustering techniques have a broad field of appli...

Clustering Based Multi-Objective Rule Mining using Genetic Algorithm

Multi-Objective Genetic Algorithm (MOGA) is a new approach for association rule mining in the market-basket type databases. Finding the frequent itemsets is the most resource-consuming phase in association rule mining, and always does some extra comparisons against the whole database. This paper proposes a new algorithm, Cluster-Based MultiObjective Genetic Algorithm (CBMOGA) which optimizes th...