نتایج جستجو برای: nsga ii metaheuristic algorithm

تعداد نتایج: 1314299  

Journal: :Appl. Soft Comput. 2015
Indranil Pan Saptarshi Das

Fractional-order proportional-integral-derivative (FOPID) controllers are designed for load-frequency control (LFC) of two interconnected power systems. Conflicting time-domain design objectives are considered in a multi-objective optimization (MOO)-based design framework to design the gains and the fractional differ-integral orders of the FOPID controllers in the two areas. Here, we explore th...

Journal: :IEEE Access 2023

Appropriate renewable distributed generation (RDG) placement is one of the most significant issues for efficient operation current power systems. Since inverter-interfaced RDG lacks rotating mass to sustain system’s inertia, microgrids have low total system which impairs frequency stability and can yield voltage instability in severe disruptions. The virtual synchronous generator (VSG), uses co...

2016
Edgar Galván López Efrén Mezura-Montes Ouassim Ait ElHara Marc Schoenauer

Research on semantics in Genetic Programming (GP) has increased dramatically over the last number of years. Results in this area clearly indicate that its use in GP can considerably increase GP performance. Motivated by these results, this paper investigates for the first time the use of Semantics in Muti-Objective GP within the well-known NSGA-II algorithm. To this end, we propose two forms of...

2010
Deepak Sharma Pierre Collet

In this paper, a GPGPU (general purpose graphics processing unit) compatible Archived based Stochastic Ranking Evolutionary Algorithm (G-ASREA) is proposed, that ranks the population with respect to an archive of non-dominated solutions. It reduces the complexity of the deterministic ranking operator from O(mn) to O(man) and further speeds up ranking on GPU. Experiments compare G-ASREA with a C...

Bahare Asgarian Hamed Farrokhi-Asl Masoud Rabbani

It is observed that the separated design of location for depots and routing for servicing customers often reach a suboptimal solution. So, solving location and routing problem simultaneously could achieve better results. In this paper, waste collection problem is considered with regard to economic and societal objective functions. A non-dominated sorting genetic algorithm (NSGA-II) is used to l...

2000
Kalyanmoy Deb Samir Agrawal Amrit Pratap T. Meyarivan

Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) O(mN3) computational complexity (where m is the number of objectives and N is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary algo...

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 ...

2016
Boxiong Tan Hui Ma Mengjie Zhang

In recent years, web services technology is becoming increasingly popular because of the convenience, low cost and capacity to be composed into high-level business processes. The service location-allocation problem for a web service provider is critical and urgent, because some factors such as network latency can make serious effect on the quality of service (QoS). This paper presents a multi-o...

2007
Wei Peng Qingfu Zhang Hui Li

Most multiobjective evolutionary algorithms are based on Pareto dominance for measuring the quality of solutions during their search, among them NSGA-II is well-known. A very few algorithms are based on decomposition and implicitly or explicitly try to optimize aggregations of the objectives. MOEA/D is a very recent such an algorithm. One of the major advantages of MOEA/D is that it is very eas...

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