dynamic economic load dispatch is one of the most important roles of power generation’s operation and control. it determines the optimal controls of production of generator units with predicted load demand over a certain period of time. economic dispatch at minimum production cost is one of the most important subjects in the power network’s operation, which is a complicated nonlinear constraine...

The paper presents a novel Modulated Power Filter and Compensator (MPFC) scheme for voltage stability, energy conservation, loss reduction, power factor correction, and power quality enhancement for electric distribution systems based on Multi-Objective Particle Swarm Optimisation (MOPSO). The MPFC scheme was developed by the first author to vary the shunt power filter equivalent admittance, mo...

Method: A global search Particle Swarm Optimization (PSO) model is then established based on cluster analysis and grey theory. The three main operational mechanisms are: (1) an external repository to retain the optimal non-dominated solution set; (2) combined cluster analysis and grey theory to ensure a better distribution of the non-dominated solution search process; and (3) a virtual circle c...

Efficient portfolio design is a principal challenge in modern computational finance. Optimization based on Markowitz two-objective mean-variance approach is computationally expensive for real financial world. Practical portfolio design introduces further complexity as it requires the optimization of multiple return and risk measures. Some of these measures are nonlinear and nonconvex. The probl...

Mathematical programming and artificial intelligence (AI) methods are known as the most effective and applicable procedures to form manufacturing cells in designing a cellular manufacturing system (CMS). In this paper, a bi-objective programming model is presented to consider the cell formation problem that is solved by a proposed multi-objective particle swarm optimization (MOPSO). The model c...

In multiobjective particle swarm optimization (MOPSO), the global-best is randomly selected for each population from a nondominated solution set. However, this Roulette wheel-based global selection ineffective convergence and diversity when problem has numerous decision variables or large number of candidates. Thus, study proposes cluster-based MOPSO (CMOPSO). CMOPSO, similarities between parti...

Reconfigurable Manufacturing System (RMS) justifies the need of hour by combining the high throughput of dedicated manufacturing system with the flexibility of flexible manufacturing systems. At the heart of RMS lies the Reconfigurable Machine Tools which are capable of performing multiple operations in its existing configurations and can further be reconfigured into more configurations which m...

The traditional way of scheduling production processes often focuses on profit-driven goals (such as cycle time or material cost) while tending to overlook the negative impacts of manufacturing activities on the environment in the form of carbon emissions and other undesirable by-products. To bridge the gap, this paper investigates an environment-aware production scheduling problem that arises ...

The purpose of this research is predicting the stock prices using the Particle Swarm Optimization Algorithm and Box-Jenkins method. In this way, the information of 165 corporations is collected from 2001 to 2016. Then, this research considers price to earnings per share and earnings per share as main variables. The relevant regression equation was created using two variables of earnings per sha...