نتایج جستجو برای: dominate sorting genetic algorithm ii

تعداد نتایج: 1873964  

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...

2011
Michael Mazurek Slawomir Wesolkowski Paul Comeau

....... An important problem in the realm of evolutionary multi-objective optimization (MOO) is that of finding all non-dominated fronts (NDFs). We specifically address the computational efficiency of the non-dominated sorting algorithm for finding the non-dominated fronts for the non-dominated sorting genetic algorithm II (NSGA-II) algorithm. We introduce the Limiting Index Sort (LIS) algorith...

Journal: :Evolutionary computation 2008
Hongbing Fang Qian Wang Yi-Cheng Tu Mark F. Horstemeyer

We present a new non-dominated sorting algorithm to generate the non-dominated fronts in multi-objective optimization with evolutionary algorithms, particularly the NSGA-II. The non-dominated sorting algorithm used by NSGA-II has a time complexity of O(MN(2)) in generating non-dominated fronts in one generation (iteration) for a population size N and M objective functions. Since generating non-...

A redundancy allocation problem (RAP) is a well-known NP-hard problem that involves the selection of elements and redundancy levels to maximize the system reliability under various system-level constraints. In many practical design situations, reliability apportionment is complicated because of the presence of several conflicting objectives that cannot be combined into a single-objective functi...

M. Beigi V. R. Ghezavati

During the last decade, the stringent pressures from environmental and social requirements have spurred an interest in designing a reverse logistics (RL) network. The success of a logistics system may depend on the decisions of the facilities locations and vehicle routings. The location-routing problem (LRP) simultaneously locates the facilities and designs the travel routes for vehicles among ...

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: :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...

The hub location problem is employed for many real applications, including delivery, airline and telecommunication systems and so on. This work investigates on hierarchical hub network in which a three-level network is developed. The central hubs are considered at the first level, at the second level, hubs are assumed which are allocated to central hubs and the remaining nodes are at the third ...

B. M. Vishkaei, M. EbrahimNezhad Moghadam Rashti, R. Esmaeilpour,

Abstract In general redundancy allocation problems the redundancy strategy for each subsystem is predetermined. Tavakkoli- Moghaddam presented a series-parallel redundancy allocation problem with mixing components (RAPMC) in which the redundancy strategy can be chosen for individual subsystems. In this paper, we present a bi-objective redundancy allocation when the redundancy strategies for...

Journal: تحقیقات مالی 2018

Objective: In general, financial time series such as stock indexes have nonlinear, mutable and noisy behavior. Structural and statistical models and machine learning-based models are often unable to accurately predict series with such a behavior. Accordingly, the aim of the present study is to present a new hybrid model using the advantages of the GMDH method and Non-dominated Sorting Genetic A...

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