14 research outputs found
Optimal design of microgrid-based resilient hybrid electric vehicle station by considering uncertainties
No full textDesigning a resilient hybrid electric vehicle station that integrates battery electric vehicle (BEV) charging and hydrogen refueling, supported by renewable energy sources and hybrid storage systems, is a forward-thinking approach to sustainable transportation infrastructure. This design not only improves energy security but also contributes to environmental sustainability. The system, in terms of local energy sources, consists of solar, wind, battery, and hydrogen storage systems. To design the system optimally, considering uncertainties arising from renewable generation variability, vehicle demand fluctuations, and electricity market prices, a two-stage stochastic programming model is utilized, integrating Conditional Value-at-Risk (CVaR) to explicitly address extreme tail risks linked to demand jumps and generation inconsistencies. We conduct a performance evaluation of the designed system under varying grid connection capacities, resilience constraints, and charger configurations. The analysis reveals significant trade-offs among system resilience, investment costs, and operational profitability.</p
Identical parallel machine scheduling with discrete additional resource and an application in audit scheduling
No full textResource scheduling has been one of the most prominent problems due to its technical challenges and prevalence in real-life. In this paper, we focus on an extension of the parallel machine scheduling problem with additional resources, which can be classified as a static resource-constrained parallel machine scheduling problem with unspecified job-machine assignment. The novelty of the problem we tackle stems from the additional resource that consists of components with discrete levels. The allocation of this resource to machines induces general covering constraints. This distinct characteristic of the additional resource also arises in a real-life audit scheduling problem, in which local branches of a financial firm are to be audited by a set of auditors with different experience levels. The quantification of the auditor experience and the branch experience requirement enable us to model this problem as an extension of the aforementioned scheduling problem with extra constraints related to the auditing process. We propose mathematical models for these problems and two constructive heuristic algorithms. The upper bounds attained by these algorithms are improved by a tabu-search algorithm, and an efficient lower bounding technique is developed for comparative purposes. We conduct extensive computational experiments to assess the performance of the proposed algorithms
Integrating Individual and Aggregate Diversity in Top-N Recommendation
No full textRecommender systems have become one of the main components of web technologies that help people to cope with information overload. Based on the analysis of past user behavior, these systems filter items according to users' likes and interests. Two of the most important metrics used to analyze the performance of these systems are the accuracy and diversity of the recommendation lists. Whereas all the efforts exerted in the prediction of the user interests aim at maximizing the former, the latter emerges in various forms, such as diversity in the lists across all user recommendation lists, referred to as aggregate diversity, and diversity in the lists of individuals, known as individual diversity. In this paper, we tackle the combination of these three objectives and justify this approach by showing through experiments that handling these objectives in pairs does not yield satisfactory results in the third one. To that end, we develop a mathematical model that is formulated using multiobjective optimization approaches. To cope with the intractability of this nonlinear integer programming model, its special structure is exploited by a decomposition technique. For the solution of the resulting formulation, we propose an iterative framework that is composed of a clique-generating genetic algorithm, a constructive heuristic, and an improvement heuristic. The former is designed to incorporate all objective functions into the generated cliques and specifically impose a certain level of individual diversity, whereas the latter chooses one clique for each user such that the desired aggregate diversity level is fulfilled. We conduct experiments on three data sets and show that the proposed modeling approach successfully handles all objectives according to the needs of the system and that the proposed methodology is capable of yielding good upper bounds
Evaluation of the Effect of Weather Conditions on Optimal Sizing of an Isolated Microgrid
No full textEnergy Investment Planning at a Private Company: A Mathematical Programming-Based Model and Its Application in Turkey
No full textSemra Ağralı (MEF Author)We consider a mid-sized private electricity generating company that plans to enter the market that is partially regulated. There is a cap and trade system in operation in the industry. There are nine possible power plant types that the company considers to invest on through a planning horizon. Some of these plants may include a carbon capture and storage technology. We develop a stochastic mixed-integer linear program for this problem where the objective is to maximize the expected net present value of the profit obtained. We include restrictions on the maximum and minimum possible amount of investment for every type of investment option. We also enforce market share conditions such that the percentage of the total investments of the company over the total installed capacity of the country stay between upper and lower bounds. Moreover, in order to distribute the investment risk, the percentage of each type of power plant investment is restricted by some upper bound. We tested the model for a hypothetical company operating in Turkey. The results show that the model is suitable to be used for determining the investment strategy of the company.WOS:0004132478000032-s2.0-85037056874Science Citation Index Expanded - Social Sciences Citation IndexArticleUluslararası işbirliği ile yapılmayan - HAYIRKasımYÖK - 2017-1
How Data-Driven Entrepreneur Analyzes Imperfect Information for Business Opportunity Evaluation
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