نتایج جستجو برای: multi objective cat swarm optimization

تعداد نتایج: 1282705  

Journal: :Journal of Information and Communication Technology (JICT) Vol.20, No.2, April 2021 2021

Journal: :Science China-technological Sciences 2022

The selection of global best (Gbest) exerts a high influence on the searching performance multi-objective particle swarm optimization algorithm (MOPSO). candidates MOPSO in external archive are always estimated to select Gbest. However, most estimation methods, considered as Gbest fixed way, which is difficult adapt varying evolutionary requirements for balance between convergence and diversity...

2016
He Dandan

As the computer technology improves rapidly, the scale of software has increased greatly, which makes it more and more difficult to find a bug in software. As a result, the enhancement of software quality and reliability has become an important task in the field of software engineering. Test is an important step that guarantees software quality and reliability. We put forward a novel multi-obje...

2010
Robin McDougall Scott Nokleby

A distributed variant of multi-objective particle swarm optimization called multi-objective parallel asynchronous particle swarm optimization (MOPAPSO) was used to develop a new optimization-based synthesis routine for Grashof mechanisms. By using a formal multi-objective handling scheme based on Pareto dominance criteria, the need to pre-weight competing objective functions is removed and the ...

In present study, a three-step multi-objective optimization algorithm of cyclone separators is catered for the design objectives. First, the pressure drop (Dp) and collection efficiency (h) in a set of cyclone separators are numerically evaluated. Secondly, two meta models based on the evolved Group Method of Data Handling (GMDH) type neural networks are regarded to model the Dp and h as the re...

2010
Mardé Helbig Andries Petrus Engelbrecht

Optimisation problems occur in many situations and aspects of modern life. In reality, many of these problems are dynamic in nature, where changes can occur in the environment that influence the solutions of the optimisation problem. Many methods use a weighted average approach to the multiple objectives. However, generally a dynamic multi-objective optimisation problem (DMOOP) does not have a ...

Journal: :civil engineering infrastructures journal 0
b. kamali phd. student, college of civil and environmental engineering, amirkabir university of technology, p.o. box: 15875-4413, tehran, iran. s.j. mousavi associate professor, college of civil and environmental engineering, amirkabir university of technology, tehran, iran. p.o. box: 15875-4413, tehran, iran.

estimation of parameters of a hydrologic model is undertaken using a procedure called “calibration” in order to obtain predictions as close as possible to observed values. this study aimed to use the particle swarm optimization (pso) algorithm for automatic calibration of the hec-hms hydrologic model, which includes a library of different event-based models for simulating the rainfall-runoff pr...

2016
Adel H. Al-Mter Songfeng Lu Yahya E. A. Al-Salhi Arkan A. G. Al-Hamodi

A Multi-objective problems occurs wherever optimal solution necessary to be taken in the presence of tradeoffs between more than one conflicting objectives. Usually the population’s values of MOPSO algorithm are random which leads to random search quality. Particle Swarm Optimization Based on Multi Objective Functions with Uniform Design (MOPSO-UD), is proposed to enhance the accuracy of the pa...

Journal: :international journal of smart electrical engineering 0
naser ghorbani eastern azarbayjan electric power distribution company ebrahim babaei university of tabriz

this paper proposes the exchange market algorithm (ema) to solve the combined economic and emission dispatch (ceed) problems in thermal power plants. the ema is a new, robust and efficient algorithm to exploit the global optimum point in optimization problems. existence of two seeking operators in ema provides a high ability in exploiting global optimum point. in order to show the capabilities ...

2006
Hongbo Liu Ajith Abraham Okkyung Choi Seong Hwan Moon

This paper introduces a hybrid metaheuristic, the Variable Neighborhood Particle Swarm Optimization (VNPSO), consisting of a combination of the Variable Neighborhood Search (VNS) and Particle Swarm Optimization(PSO). The proposed VNPSO method is used for solving the multi-objective Flexible Job-shop Scheduling Problems (FJSP). The details of implementation for the multi-objective FJSP and the c...

نمودار تعداد نتایج جستجو در هر سال

با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید