vendor selection decisions are complicated by the fact that various conflicting multi-objective factors must be considered in the decision making process. the problem of vendor selection becomes still more compli-cated with the inclusion of incremental discount pricing schedule. such hard combinatorial problems when solved using meta heuristics produce near optimal solutions. this paper propose...

a three stage production system is considered in this paper. there are two stages to fabricate and ready the parts and an assembly stage to assembly the parts and complete the products in this system. suppose that a number of products of different kinds are ordered. each product is assembled with a set of several parts. at first the parts are produced in the first stage with parallel machines a...

MULTI-OBJECTIVE OPTIMIZATION OF BLAST SIMULATION USING SURROGATE MODEL Toshihiro Tsuga, M.S. George Mason University, 2007 Thesis Director: Dr. Rainald Löhner A multi objective optimization approach using a Kriging model coupled with a Multi Objective Genetic Algorithm (MOGA) is applied to a blast damage maximization problem composed of two objectives, namely number of casualties and damage to ...

In this paper, we propose a new genetic algorithm for multi-objective optimization problems. That is called “Neighborhood Cultivation Genetic Algorithm (NCGA)”. NCGA includes the mechanisms of other methods such as SPEA2 and NSGA-II. Moreover, NCGA has the mechanism of neighborhood crossover. Because of the neighborhood crossover, the effective search can be performed and good results can be de...

Multi-label spatial classification based on association rules with Multi objective genetic algorithms (MOGA) is proposed to deal with multiple class labels problem which is hard to settle by existing methods. In this paper we adapt problem transformation for the Multi label classification. We use Hybrid evolutionary algorithm for the optimization in the generation of spatial association rules, ...

37 Abstract — Feature selection (FS) is considered to be an important preprocessing step in machine learning and pattern recognition, and feature evaluation is the key issue for constructing a feature selection algorithm. Feature selection process can also reduce noise and this way enhance the classification accuracy. In this article, feature selection method based on ∩ fuzzy similarity measure...

In this paper, a combination method has been developed by coupling Multi-Objective Genetic Algorithms (MOGA) and Finite Element Method (FEM). This method has been applied for determination of the optimal stacking sequence of laminated composite plate against buckling. The most important parameters in optimization of a laminated composite plate such as, angle, thickness, number, and material of ...

controller design and optimization problems, with more than one objective, are referred as multiple objectives or multiple attributed problems. in this paper, a novel method is proposed for designing optimum pid controller that is called genetic multiple attributed decision making method (gmadm). this method is newer than the previous methods and in this paper some options are considered that h...

PurposeThe purpose of this paper is to present a hierarchical circuit synthesis system with a Hybrid DLO-MOGA (Deterministic Local Optimization Multi-Objective Genetic Algorithm) optimization scheme for system level synthesis. Design/methodology/approachThe use of a local optimization with a deterministic algorithm based on linear equations which is computationally efficient and improves the fe...

This paper presents the nonlinear time series prediction using Lyapunov theory-based fuzzy neural network and multi-objective genetic algorithm (MOGA). The architecture employs fuzzy neural network (FNN) structure and the tuning of the parameters of FNN using the combination of the MOGA and the modified Lyapunov theory-based adaptive filtering algorithm (LAF). The proposed scheme has been used ...