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.
The planning of maintenance activities can hinder manufacturing operations in term of cost, quality and time, but it is necessary to ensure the availability of the production equipment to meet customer demands. We propose to model the function of maintenance tasks and production operations by the sum of the two costs under a set of constraints. As a method of resolution, we use genetic algorithms...
In this paper, Genetic Algorithm (GA) is used to solve the Unit Commitment (UC) Problem. Unit commitment problem was formulated with consideration of up & down time, startup cost (Hot & Cold start), and production cost. Unit commitment schedule as well as economic dispatch is obtained to obtain total cost of generation. Problem specific operators are used in the algorithm to improve the quality...
In this paper, we consider a serial production line consisting of n unreliable machines with n-1 buffers. The objective is to determine the optimal preventive maintenance policy, the optimal selection of machines and the optimal buffer allocation that will minimize the total system cost subject to a given system throughput level. We assume that the mean time between failures (MTBF) of all machines...
A problem of optimal capacity planning of the process production lines (foundry for example) in accordance with a given output plan is considered as a discrete location problem on a network. The problem takes into account the terms of output plan completion for each kind of product and constraints of distribution uniformity of the total daily volume of production. For solving the problem, we use the...
Complex process modeling and optimization system is a hot area of research. A system model is proposed between process parameters and performance index by using the BP neural network for hydrogen cyanide (HCN) production process. In proposed method, the optimal process parameters would be searched by using genetic algorithm and these optimal parameters could be entered into BP neural network to predict...
Location and sizing of photovoltaic plant from the aspect of independent power market participant are studied. Of the two methods developed, the first one is based on the DC network model and the second one relies on full AC model of the network. Genetic algorithm with the twofold objective function is used. The first goal is to locate the network node with the maximum available transfer capability...
This paper deals with the production planning and control of a single product involving combined manufacturing and remanufacturing operations. We investigate here a lot-sizing problem in which the demand for items can be satisfied by both the new and the remanufactured products. We assume that produced and recovered (repaired or remanufactured) items are of the same quality. Two types of inventories...
Europe is rapidly expanding its offshore wind energy capacity. Hence, the construction of a multi-terminal dc (MTDC) infrastructure to accommodate the generated electrical energy brings several advantages, but also comes with many challenges. Operation and control of a MTDC network is one of these challenges. This paper explains the operation and control of MTDC networks. Moreover, a study is carried...
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.