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نتیجه جستجو - Cost target

تعداد مقالات یافته شده: 2
ردیف عنوان نوع
1 Optimizing a production-inventory system under a cost target
بهینه سازی سیستم موجودی تولید تحت هدف هزینه-2020
Achieving cost targets is a major concern for business managers. In this paper, we consider two risk man- agement criteria for a production-inventory system under a cost target: Probability of Loss and Expected Loss. We study two models with stochastic demand and production: The unit stockout cost model and the backlogging cost rate model. We analyze a limited-information setting that is an excellent approxi- mation to a full-information setting. We discover that the optimal inventory decisions for minimizing probability of loss are identical for both models, and that the optimal inventory decisions for minimizing expected loss share a similar structure for both models. In addition, we investigate inventory decisions when minimizing the expected cost subject to a probability of loss constraint. Extension to a generally-distributed unit production time is also explored. We provide comparative statics and manage- rial insights of value to loss-aware managers.© 2020 Elsevier Ltd. All rights reserved.
Keywords: Risk management | Cost target | Inventory | Demand-capacity interaction
مقاله انگلیسی
2 Dynamic energy conversion and management strategy for an integrated electricity and natural gas system with renewable energy: Deep reinforcement learning approach
استراتژی مدیریت و تبدیل انرژی پویا برای یک سیستم برق و گاز طبیعی یکپارچه با انرژی تجدید پذیر: رویکرد یادگیری تقویتی عمیق-2020
With the application of advanced information technology for the integration of electricity and natural gas systems, formulating an excellent energy conversion and management strategy has become an effective method to achieve established goals. Differing from previous works, this paper proposes a peak load shifting model to smooth the net load curve of an integrated electricity and natural gas system by coordinating the operations of the power-to-gas unit and generators. Moreover, the study aims to achieve multi-objective optimization while considering the economy of the system. A dynamic energy conversion and management strategy is proposed, which coordinates both the economic cost target and the peak load shifting target by adjusting an economic coefficient. To illustrate the complex energy conversion process, deep reinforcement learning is used to formulate the dynamic energy conversion and management problem as a discrete Markov decision process, and a deep deterministic policy gradient is adopted to solve the decision-making problem. By using the deep reinforcement learning method, the system operator can adaptively determine the conversion ratio of wind power, power-to-gas and gas turbine operations, and generator output through an online process, where the flexibility of wind power generation, wholesale gas price, and the uncertainties of energy demand are considered. Simulation results show that the proposed algorithm can increase the profit of the system operator, reduce wind power curtailment, and smooth the net load curves effectively in real time.
Keywords: Renewable energy accommodation | Dynamic energy conversion and management | Deep reinforcement learning
مقاله انگلیسی
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