نتایج جستجو برای: dominated sorting genetic algorithm nsga_ii and multi

تعداد نتایج: 17053689  

2013
Archana Chowdhury Amit Konar Pratyusha Rakshit Atulya K. Nagar

Proteins interact with each other in a highly specific manner, and protein interactions play a key role in many cellular processes. Since protein interactions determine the outcome of most cellular processes, so identifying and characterizing Protein– Protein interactions and their networks are essential for understanding the mechanisms of biological processes on a molecular level. This paper e...

2006
Antony W. Iorio Xiaodong Li

Multi-objective problems with parameter interactions can present difficulties to many optimization algorithms. We have investigated the behaviour of Simplex Crossover (SPX), Unimodal Normally Distributed Crossover (UNDX), Parent-centric Crossover (PCX), and Differential Evolution (DE), as possible alternatives to the Simulated Binary Crossover (SBX) operator within the NSGA-II (Non-dominated So...

2005
Ramesh Rajagopalan Chilukuri K. Mohan Kishan G. Mehrotra Pramod K. Varshney

A new evolutionary multi-objective crowding algorithm (EMOCA) is evaluated using nine benchmark multiobjective optimization problems, and shown to produce non-dominated solutions with significant diversity, outperforming state-of-the-art multi-objective evolutionary algorithms viz., Non-dominated Sorting Genetic Algorithm – II (NSGA-II), Strength Pareto Evolutionary algorithm II (SPEA-II) and P...

2013
J. Moshtagh S. Ghasemi

In this paper, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) based approach is presented for distribution system reconfiguration. In contrast to the conventional GA based methods, the proposed approach does not require weighting factors for conversion of multi-objective function into an equivalent single objective function. In order to illustrate the performance of the proposed method,...

2010
Vladimír ŠEDĚNKA Zbyněk RAIDA

The paper deals with efficiency comparison of two global evolutionary optimization methods implemented in MATLAB. Attention is turned to an elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and a novel multi-objective Particle Swarm Optimization (PSO). The performance of optimizers is compared on three different test functions and on a cavity resonator synthesis. The microwave resonator...

2014
Remica Aggarwal Ainesh Bakshi

This paper proposes a Stochastic Chance-Constrained Programming Model (SCCPM) for the supplier selection problem to select best suppliers offering incremental volume discounts in a conflicting multi-objective scenario and under the event of uncertainty. A Fast Non-dominated Sorting Genetic Algorithm (NSGA-II), a variant of GA, adept at solving Multi Objective Optimization, is used to obtain the...

2017
T. Rabczuk

Corresponding Author: Rabczuk, T./Ilyani Akmar, A.B. Institute of Structural Mechanics, Bauhaus University of Weimar, Marienstrasse 15, 99423 Weimar, Germany Faculty of Civil Engineering, MARA University of Technology, 40450 Shah Alam, Selangor, Malaysia Email: [email protected] Email: [email protected] Abstract: In this study, an application of evolutionary multi-objective o...

Optimizing gate scheduling at airports is an old, but also a broad problem. The main purpose of this problem is to find an assignment for the flights arriving at and departing from an airport, while satisfying a set of constraints.A closer look at the literature in this research line shows thatin almost all studies airport gate processing time has been considered as a fix parameter. In this res...

ژورنال: انرژی ایران 2018

In this study, a combined cycle power plant with a nominal capacity of 500 MW, including two gas units and one steam unit, was considered by the mathematical model of thermodynamic modeling and the results of the modeling were controlled by the design information of the system. Then, the objective functions are optimized by considering the decision variables. In this multi-objective optimizatio...

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