نتایج جستجو برای: objective particle swarm optimization mopso

تعداد نتایج: 998471  

A. Adib , I. Ahmadianfar, M. Taghian,

To deal with severe drought when water supply is insufficient hedging rule, based on hedging rule curve, is proposed. In general, in discrete hedging rules, the rationing factors have changed from a zone to another zone at once. Accordingly, this paper is an attempt to improve the conventional hedging rule to control the changes of rationing factors. In this regard, the simulation model has emp...

2013
Karim Salahshoor Kamal Jafarian

Gas turbines can be found in many industrial application areas. Gas turbine generation is limited by some undesirable effects which can be incorporated as operational constraints. Because of importance of energy, optimization of power generation systems is necessary. In order to achieving higher efficiencies, some propositions are preferred such as recovery of heat from exhaust gases in a regen...

Journal: :Applied Mathematics and Computer Science 2017
Cili Zuo Lianghong Wu Zhao-Fu Zeng Hua-Liang Wei

The fruit fly optimization algorithm (FOA) is a global optimization algorithm inspired by the foraging behavior of a fruit fly swarm. In this study, a novel stochastic fractal model based fruit fly optimization algorithm is proposed for multiobjective optimization. A food source generating method based on a stochastic fractal with an adaptive parameter updating strategy is introduced to improve...

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 ...

Journal: :Journal of Industrial and Management Optimization 2022

<p style='text-indent:20px;'>A combined location-routing-inventory system (CLRIS) in a three-echelon supply chain network is studied with environmental considerations. Specifically, bi-objective mixed integer programming model formulated for the CLRIS to deal trade-offs between total cost and carbon-capped difference (CCD). A multi-objective particle swarm optimization (MOPSO) heuristic s...

Journal: :J. Simulation 2015
M. Güller Y. Uygun B. Noche

One of the most important aspects affecting the performance of a supply chain is the management of inventories. Managing inventory in complex supply chains is typically difficult, and may have a significant impact on the customer service level and system-wide costs. The main challenge of inventory management is that almost every inventory problem involves multiple and conflicting objectives tha...

2012
Ki-Baek Lee Jong-Hwan Kim

This paper proposes a homogeneous distributed computing (HDC) framework for multi-objective evolutionary algorithm (MOEA). In this framework, multiple processors divide a work into several pieces and carry them out in parallel. Every processor does its task in a homogeneous way so that the overall procedure becomes not only faster but also fault-tolerant and independent to the number of process...

2009
Adel M. Sharaf Adel A. A. El-Gammal

There is an increasing interest in renewable and green energy sources and the integration of Distributed Generation DG into the power grid system. The problem of optimal capacitor allocation in electric distribution systems involves maximizing energy utilization, feeder loss reduction, and power factor correction. The feeder loss can be separated into two parts based on the active and reactive ...

2013
Chan-Sik Kim Jong-Seong Kim

In rapidly changing market environment, firms are investing a lot of time and resources into new product development (NPD) projects to make profit and to obtain competitive advantage. However, failure rate of NPD projects is becoming high due to various internal and external risks which hinder successful NPD projects. To reduce the failure rate, it is critical that risks have to be managed effe...

Journal: :Int. J. Computational Intelligence Systems 2010
Xiangwei Zheng Hong Liu

Multi-Objective Particle Swarm Optimizers (MOPSOs) are easily trapped in local optima, cost more function evaluations and suffer from the curse of dimensionality. A scalable cooperative coevolution and -dominance based MOPSO (CEPSO) is proposed to address these issues. In CEPSO, Multi-objective Optimization Problems (MOPs) are decomposed in terms of their decision variables and are optimized b...

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