نتایج جستجو برای: mopso algorithm

تعداد نتایج: 754185  

Proper and realistic scheduling is an important factor of success for every project. In reality, project scheduling often involves several objectives that must be realized simultaneously, and faces numerous uncertainties that may undermine the integrity of the devised schedule. Thus, the manner of dealing with such uncertainties is of particular importance for effective planning. A realistic sc...

Journal: :Polymer Composites 2021

The growing dominance in terms of industrial applications has helped polymer-based composite materials conquering new markets relentlessly. But the presence fibrous residuals and abrasive particles as reinforcement polymer matrix composites (PMCs) affects output quality characteristics (OQCs) microdrilling operations. OQC aims at reducing overcuts momentous material removal rate (MRR). In such ...

Journal: :International Journal of Rf and Microwave Computer-aided Engineering 2023

In this paper, an innovative method for designing the top load of a very low frequency (VLF) thirteen-tower umbrella antenna based on multiobjective particle swarm optimization (MOPSO) is proposed. The design antenna’s mainly involves sag and position distribution cables. On basis analyzing influence cables’ radiation efficiency, MOPSO Pareto optimality used to optimize location catenaries. res...

2010
H. Safikhani S. A. Nourbakhsh A. Bagheri M. J. Mahmood Abadi

In the present study, multi-objective optimization of centrifugal pumps is performed at three steps. At the first step, η and NPSHr in a set of centrifugal pump are numerically investigated using commercial software. Two meta-models based on the evolved group method of data handling (GMDH) type neural networks are obtained, at the second step, for modeling of η and NPSHr with respect to geometr...

2016
Dongqi Liu Yaonan Wang Yongpeng Shen

This paper proposed a optimal strategy for coordinated operation of electric vehicles (EVs) charging and discharging with wind-thermal system. By aggregating a large number of EVs, the huge total battery capacity is sufficient to stabilize the disturbance of the transmission grid. Hence, a dynamic environmental dispatch model which coordinates a cluster of charging and discharging controllable ...

2006
Roselyn D. Santos

The decision tree is a popular and widely-used classification model. The two main objectives in decision tree induction are accurate predictions for unseen instances and human comprehensibility. In this paper, we use multiobjective optimization for the evolution of decision tree classifiers that are efficient both with respect to classification accuracy and classifier complexity. Simpler decisi...

This research addresses the mixed-model assembly line (MMAL) by considering various constraints. In MMALs, several types of products which their similarity is so high are made on an assembly line. As a consequence, it is possible to assemble and make several types of products simultaneously without spending any additional time. The proposed multi-objective model considers the balancing and sequ...

The problem of maximizing the benefit from a specified number of a particular product with respect to the behavior of customer choices is regarded as revenue management. This managerial technique was first adopted by the airline industries before being widely used by many others such as hotel industries. The scope of this research is mainly focused on hotel revenue management, regarding which a...

Journal: :Coatings 2021

To control the welding residual stress and deformation of metal inert gas (MIG) welding, influence process parameters preheat (welding speed, heat input, temperature, area) is discussed, a prediction model established to select optimal combination parameters. Thermomechanical numerical analysis was performed obtain according 100 × 150 50 4 mm aluminum alloy 6061-T6 T-joint. Owing complexity pro...

2010
Juan Carlos Fuentes Cabrera Carlos A. Coello Coello

In this chapter, we present a multi-objective evolutionary algorithm (MOEA) based on the heuristic called “particle swarm optimization” (PSO). This multi-objective particle swarm optimizer (MOPSO) is characterized for using a very small population size, which allows it to require a very low number of objective function evaluations (only 3000 per run) to produce reasonably good approximations of...

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