نتایج جستجو برای: dominated sorting genetic algorithm

تعداد نتایج: 1384969  

Journal: :Proceedings of the ... AAAI Conference on Artificial Intelligence 2022

The non-dominated sorting genetic algorithm II (NSGA-II) is the most intensively used multi-objective evolutionary (MOEA) in real-world applications. However, contrast to several simple MOEAs analyzed also via mathematical means, no such study exists for NSGA-II so far. In this work, we show that runtime analyses are feasible NSGA-II. As particular results, prove with a population size larger t...

Journal: :Chinese journal of mechanical engineering 2022

Abstract Robot manipulators perform a point-point task under kinematic and dynamic constraints. Due to multi-degree-of-freedom coupling characteristics, it is difficult find better desired trajectory. In this paper, multi-objective trajectory planning approach based on an improved elitist non-dominated sorting genetic algorithm (INSGA-II) proposed. Trajectory function planned with new composite...

Journal: :JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) 2023

Penjadwalan operasi pasien merupakan aktifitas penting pada kegiatan operasional rumah sakit, karena menentukan waktu pasien-pasien tertangani dengan baik. Permasalahan ini dimodelkan sebagai masalah optimasi multi-obyektif yaitu meminimalkan yang digunakan saat tindakan operasi. Masalah penjadwalan dirumuskan mixed integer programming (MIP), sehingga variabel merepresentasikan jadwal kasus lay...

2005
Daniel Kunkle

The following MOEA algorithms are briefly summarized and compared: • NPGA Niched Pareto Genetic Algorithm (1994) – NPGA II (2001) • NSGA Non-dominated Sorting Genetic Algorithm (1994) – NSGA II (2000) • SPEA Strength Pareto Evolutionary Algorithm (1998) – SPEA2 (2001) – SPEA2+ (2004) – ISPEA Immunity SPEA (2003) • PAES Pareto Archived Evolution Strategy (2000) – M-PAES Mimetic PAES (2000) • PES...

2001
Seungwon Lee R. J. Terrile

We address the problem of optimizing a spacecraft trajectory by using three different multi-objective evolutionary algorithms: i) Non-dominated sorting genetic algorithm, ii) Pareto-based ranking genetic algorithm, and iii) Strength Pareto genetic algorithm. The trajectory of interest is an orbit transfer around a central body when the spacecraft uses a lowthrust propulsion system. We use a Lya...

2013
Abolfazl Golshan Amran Ayob

In this study, two parameters of surface roughness and volumetric material removal rate are optimized based on computational intelligence method. Wire electrical discharge machine is used for machining of cold-work steel 2601. The relation between Input parameters including electrical current, pulse-off time, open-circuit voltage and gap voltage and output parameters is studied via Experimental...

2013
Hassan Jafari Maryam Mahmoudi Abbas Rabiee

Static Var compensator (SVC) is one of flexible AC transmission system (FACTS) elements mainly used for reactive power and voltage control in power systems. This paper deals with multi-modal electromechanical oscillations damping in the presence of severe disturbances. These oscillations include local modes, interarea modes and inter-plant modes. To enhance the damping of the oscillations, a co...

A multi-objective optimization (MOO) of two-element wing models with morphing flap by using computational fluid dynamics (CFD) techniques, artificial neural networks (ANN), and non-dominated sorting genetic algorithms (NSGA II), is performed in this paper. At first, the domain is solved numerically in various two-element wing models with morphing flap using CFD techniques and lift (L) and drag ...

Ever-increasing energy demand has led to geographic expansion of transmission lines and their complexity. In addition, higher reliability is expected in the transmission systemsdue to their vital role in power systems. It is very difficult to realize this goal by conventional monitoring and control methods. Thus, phasor measurement units (PMUs) are used to measure system parameters. Although in...

This study introduces a green location, routing and inventory problem with customer satisfaction, backup distribution centers and risk of routes in the form of a non-linear mixed integer programming model. In this regard, time window is considered to increase the customer satisfaction of the model and transportation risks is taken into account for the reliability of the system. In addition, dif...

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