The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper presents an optimized scheduling method for Plugged-in Electric Vehicles (PEV) that are connected to a residential smart microgrid. Two modes of operation are studied: grid-tied and islanded mode. A Genetic Algorithm (GA)-based method is utilized to optimize an objective function, which includes the cost of energy production, and guarantees the best possible energy consumption profile....
The approaches for the parametric synthesis of the automatic control system (ACS) using the genetic algorithm that performs an approximation of Pareto-optimal solutions set are suggested. As a result, two approaches to multi-criteria optimization of ACS were considered: (1) the optimization problem was considered to be three-criteria for equally important criteria, (2) the optimization problem was...
In the machining process, the rationalization of the cutting amount is an important way to effectively improve the productivity, reduce the cost and improve the quality of the workpiece. The rapid development of genetic algorithm has made remarkable achievements in solving the problem of nonlinear optimization. However, in the process of machining, there are many factors that affect the amount of...
Bilevel optimization refers to a hierarchical problem in which optimization needs to be performed at two nested levels, namely the upper level and the lower level. The aim is to identify the optimum of the upper level problem, subject to optimality of the corresponding lower level problem. Several problems from the domain of engineering, logistics, economics, and transportation have inherent nested...
The workforce planning helps organizations to optimize the production process with aim to minimize the assigning costs. A workforce planning problem is very complex and needs special algorithms to be solved. The problem is to select set of employers from a set of available workers and to assign this staff to the jobs to be performed. Each job requires a time to be completed. For efficiency, a worker...
This paper proposes an efficient methodology to optimally determine the best location and optimum size for Distributed Generators (DG), in a distribution network, while minimizing energy losses and improving voltage profile. The proposed methodology has been designed to consider variable demand and variable DG production scenarios, offering a set of optimum values for DG active power output and power...
This paper conducts a comparative study on the predicted operating characteristics of a series of optimally designed concentrated-winding, V-shaped magnet Interior Permanent Magnet Synchronous Motors (IPMSMs). A local optimizer (nonlinear Simplex) and a global optimizer (Genetic Algorithm (GA)) are separately used to determine the dimensions of each optimized machine based on three distinctive Objective...
This paper proposes a novel optimization algorithm called ant-lion optimizer (ALO) for optimal distributed energy resources (DERs) allocation in various radial distribution networks. The objective function is to maximize the percentage of power losses reduction. The proposed algorithm is executed on IEEE 34 and 118-bus radial distribution networks with different number of installed DERs. The simulation...
In This paper, an improved adaptive genetic algorithm is presented for the design optimization on Permanent magnet synchronous motor(PMSM), which can availably reduce the iterative time and simplify the magnetic circuit calculation during optimization designing. To obtain higher computation speed, C++ language is applied to develop both the basic electromagnetic calculation program and optimization...
This paper uses a multi-objective optimization approach to assess building energy performance for residential homes in the Bahamas with the goal of providing objective data to policymakers to help achieve the country's sustainability goals. A non-sorting genetic algorithm (NSGA-II) is used to find optimal solutions to building design configurations such as wall types, insulation thickness, insulation...
The location problem of logistics center is the key process of logistics distribution, in order to improve the accuracy of the location of logistics center, this paper according to the parallelism and characteristics of global optimization of genetic algorithm. A method based on genetic algorithm is proposed to solve the problem of logistics center location, and set up with the minimum total cost...
Differential Evolution (DE) algorithm is well known as a simple and efficient scheme for multi-objective global optimization over continuous spaces. In order to reduce the calculation complexity and the diversity sorting quality, the modified non-dominated sorted differential evolution (MNSDE) algorithm is proposed in this paper. The individual distribution is large-ranging and well-proportion in...
In this paper we evaluate metaheuristic optimization methods on a partitional clustering task of a real-world supply chain dataset, aiming at customer segmentation. For this purpose, we rely on the automatic clustering framework proposed by Das et al. [1], named henceforth DAK framework, by testing its performance for seven different metaheuristic optimization algorithm, namely: simulated annealing...
This paper presents the study of a vacuum interrupter (VI) of 12kV, in terms of optimization of the electrical field in order to obtain a more uniform distribution inside the VI chamber. The proposed method consists in combining the construction and simulation programs in a Solid Works module, respectively ComsolMultiphisics, with the optimization module that includes the programming environment Matlab...
Vibration control of flexible structures has always been one of the most important issues and Among variant available control methods, active vibration control using piezoelectric sensors and actuators has become popular due to its high efficiency and flexibility for designing a control system. The main concern in designing a control system with piezoelectric patches is finding best position for patches...
In course of the German power system transition to a higher share of renewable energy sources decentralized activities constitute a major driving force for the growth of renewable energy capacity. In this context plural activities and initiatives on the local and regional level are followed to develop concepts for an efficient and sustainable regional energy supply. To achieve these goals various...
This article presents the digital twin concept, which is an augmented manufacturing project created in close collaboration by SOVA Digital and the Institute of Automation, Measurement and Applied Informatics (ÚAMAI), of the Faculty of Mechanical Engineering, Slovak University of Technology in Bratislava with the support of SIEMENS. The project is a technological concept focusing on the continuous...
This paper presents the results of an optimisation analysis aimed at exploring the geographical allocation of solar PV generation capacity in the context of grid support considerations such as average daily yield and variability, with particular focus on the full year scenario compared to the high demand season. All problem cases were evaluated using a combination of genetic algorithm (GA) and pattern...
We consider the problem of replicating the returns of a financial index as accurately as possible by selecting a subset of the assets that constitute the index and determining the portfolio weight of each selected asset subject to various constraints that are relevant in practice, including the UCITS III (Undertakings for Collective Investments in Transferable Securities) 5/10/40 concentration rule...
Most published results show that power reduction of the finite-state machines (FSMs) is achieved by decomposition. In order to achieve a low power FSM implementation, a Genetic Fuzzy c-mean clustering-based decomposition method, called GFCM-D, is proposed for FSM partition in this study. GFCM-D used Fuzzy c-mean clustering (FCM) to partition a set of states of FSM into a collection of c fuzzy clusters,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.