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This paper describes a decision support system (DSS) built on knowledge extraction using simulation-based optimization and data mining. The paper starts with a requirements analysis based on a survey conducted with a number of industrial companies about their practices of using simulations for decision support. Based upon the analysis, a new, interactive DSS that can fulfill the industrial requirements,...
This paper studies a multi-period demand response management problem in the smart grid where multiple utility companies compete among themselves. The user-utility interactions are modeled by a noncooperative game of a Stackelberg type where the interactions among the utility companies are captured through a Nash equilibrium. It is shown that this game has a unique Stackelberg equilibrium at which...
Business analytics techniques help mine and analyze business/financial data. For instance, a structural support vector machine (SSVM) can be used to perform classification on complex inputs such as the nodes of a graph structure. We connect collaborating companies in the information technology sector in an undirected graph and use an SSVM to predict positive or negative movement in their stock prices...
This paper presents a concept to anticipate deviations from the target process and thus inefficiencies within development projects by aid of predictive analytics. It is stated that predictive analytics approaches can be adapted to predict deviations in development projects, comparable to the anticipation of crimes. Deviations in terms of time, costs and quality are seen as a result of waste and therefore...
The article proposes a distributed reinforcement learning collaborative consensus algorithm for dynamic generation command dispatch of AGC in interconnected power grids under the framework of the virtual power generation tribes, in order to in response to the development of the EMS system in the Smart Grid from centralization to decentralized form. The simulation results of the Guangdong Grid show...
Lean and simulation analysis are driven by the same objective, how to better design and improve processes making the companies more competitive. The adoption of lean has been widely spread in companies from public to private sectors and simulation is nowadays becoming more and more popular. Several authors have pointed out the benefits of combining simulation and lean, however, they are still rarely...
In this paper is proposed a new multi-objective function include energy losses cost and reliability indices for placement of reclosers and fuses in distribution networks. All of the indices is converted to economical factors for suitable optimization and physical concept the objective function. Increasing the annual energy cost and cost of reliability indices are considered because study term is more...
A reference network is topologically identical to the existing network in which the generators and loads are not changed while the transmission line capacity will be optimized. By applying a reference network, the optimal transmission capacities of each line could be identified, as it takes annual operational and transmission costs into consideration. A reference network provides a standard to evaluate...
Design automation (DA) is at a historical moment where it has a chance — after mathematics, statistics, and computer science — to establish itself as the fourth universal approach with widespread applications in a variety of scientific, engineering, and economic domains. We start by outlining some of the most important research contributions and industrial applications of the design automation; we...
Currently, the electricity demand is exponentially increasing due to the population growth. Therefore, the demand side management (DSM) is becoming unavoidable especially with the increasing use of renewable energy sources. One of the most known tactics of DSM is the use pricing strategies to threaten users to schedule their loads by controlling their own appliances. In this paper, a new model of...
Manufacturing costs and tolerance will affect the price and the quality of a product from every manufacturer company. Companies must produce high-quality products with low manufacturing costs in order to keep their products competitive in the market. However, it is difficult to produce a high-quality product with a low manufacturing cost. Companies have difficulties in determining the components to...
Big Data is one of the most discussed trend themes worldwide in both research community and industrial practice. Thus, researchers as well as company representatives focus on the study of Big Data technologies and the potentials deriving from gaining and structuring data. In this paper, we firstly conduct a literature review. Then, we describe the approach to implement reaction management in manufacturing...
The gap between scheduling theory and practice has been long known, recognized and studied. More often than not, elaborated scheduling models and procedures are proven to be extremely effective in controlled and synthetic laboratory problems but rarely applied in practical manufacturing scheduling. Real scheduling problems are varied, big and rich in the number of constraints and special characteristics.
A social media message that is forwarded (e.g., Retweeted in Twitter) by many users may diffuse widely. Such a 'viral' message may have a major impact in the real world. If the content maligns a company, the company must respond as quickly as possible to defend its brand image. Timely knowledge about what kinds of information are diffusing in social media is thus quite important. We have developed...
We formulate an integrated design and evaluation mechanism applying techniques in the field of flexible engineering design and real options analysis to build a liquefied natural gas production and fueling system for a Singapore oil & gas company. The proposed methodology consists of four main steps: 1) design and evaluation under deterministic demand, 2) uncertainty characterization and performance...
In this paper is presented the development of an industrial application of "Directed Searching Optimization Algorithm" (for its acronym in English DSO) in a company producing automotive electrical conduction systems. The DSO is a novel alternative newly developed to solve problems of constrained optimization. So far there's not found evidence reported in the literature of the same field,...
The gap between scheduling theory and practice has been long known, recognized and studied. More often than not, elaborated scheduling models and procedures are proven to be extremely effective in controlled and synthetic laboratory problems but rarely applied in practical manufacturing scheduling. Real scheduling problems are varied, big and rich in the number of constraints and special characteristics.
The growth of electricity demand in Argentina leads to the system expansion in generation, transmission and distribution networks in that country. Regarding distribution networks, a typical problem arises when a distribution company or a large customer must choose the location of its electrical substations; because this decision will determine the total cost of the installation. With the aim of minimize...
The purpose of this paper is to evaluate the performance of a new multiobjective algorithm called Vector Evaluated Population Based Incremental Learning (VEPBIL). The new algorithm was applied in solving a real world application named Reinsurance Contract Optimization (RCO), which is a multiobjective problem consisting of maximizing two conflicting functions: expected return and risk. The VEPBIL was...
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