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IEEE International Conference on Power and Power and Renewable Energy (ICPRE)

作者： Yuzhen Sun Yuekai Li Daogang Peng Hao Zhang Shanshan Shi Chen Fang Haojing Wang Zhixin Wang Guojie Li College of Automation Engineering Shanghai University of Electric Power Shanghai China College of Electronic and Information Engineering Tongji University Shanghai China State Grid Shanghai Electric Power Company Shanghai China College of Electronic Information and Electric Engineering Shanghai Jiao tong University Shanghai China

ISBN: (数字)9781728190266

ISBN: (纸本)9781728190273

The large-scale development of electric vehicles and the increase in the proportion of renewable energy power generation are effective ways for our country to transform its low-carbon economic development model. In this paper, from the perspective of synergy between large-scale electric vehicles and renewable energy power generation, comprehensively considering the characteristics of the randomness of electric vehicle loads and the intermittency of renewable energy, the two cooperative interaction technologies are studied. The electric vehicle (EV)-photovoltaic power generation (PPG) collaborative interactive dynamic programming model is optimized using hybrid particle swarm optimization algorithm (BreedPSO). Finally, the data of a certain Shanghai area are simulated and analyzed. The results show that the access of electric vehicles can effectively suppress grid load fluctuations and reduce the system load variance.

关键词： electric vehicle renewable energy collaborative interaction dynamic programming model BreedPSO Electric vehicles renewable energy power generation Renewable energy SRGN gene dynamic programming Load fluctuation Solar power generation Nuclear power generation intermittency

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A scenario-based dynamic programming model for multi-period liner ship fleet planning

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2011年第4期47卷 401-413页

作者： Meng, Qiang Wang, Tingsong Natl Univ Singapore Dept Civil Engn Singapore 117576 Singapore

This paper proposes a more realistic multi-period liner ship fleet planning problem for liner container shipping company than has been studied in previous literature. The proposed problem is formulated as a scenario-based dynamic programming model consisting of a number of integer linear programming formulations for each single planning period, and the model can be solved efficiently by a shortest path algorithm on an acyclic network. A numerical example is carried out to illustrate the applicability of the proposed model and solution method. The numerical results show that chartering in ships may not always be a better policy for a long-term planning horizon though it is much cheaper than buying ships in the short-term. Purchasing ships seems to be a more profitable investment in the long run. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Multi-period liner ship fleet planning Scenario decision tree dynamic programming model Integer linear programming model

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Expected hesitant VaR for tail decision making under probabilistic hesitant fuzzy environment

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APPLIED SOFT COMPUTING 2017年 60卷 297-311页

作者： Zhou, Wei Xu, Zeshui Yunnan Univ Finance & Econ Sch Finance Kunming 650221 Yunnan Peoples R China Sichuan Univ Businees Sch Chengdu 610064 Sichuan Peoples R China

Generally, to reasonably make decision, all evaluation information should be aggregated, and thus, the ranking and the optimal alternative can be obtained. However, in some extreme cases, the decision maker (DM) can only focus on the tail information such as the big-loss or big-gain values and wants to ask the simple question "How bad can a thing become?" or "How good can a thing become?" To address this type of decision-making issue, this paper introduces the definition of value at risk (VaR), which is a famous term in the financial field, and the probabilistic hesitant fuzzy element (PHFE), which is a general hesitant fuzzy element (HFE) and has recently become a popular topic. Then, the hesitant VaR (HVaR) is defined, and its mathematical presentation is provided to measure the tail information of the PHFEs. It is found that the tail information calculated by the HVaR is segmentary, and only the boundary value is used. Therefore, this paper further develops the expected HVaR (EHVaR) to improve the HVaR, which can describe the entire tail information. Two simple examples are provided to show and compare the proposed HVaR and EHVaR. To apply the EHVaR into a group decision making that focuses on the tail information, this paper proposes a dynamic programming model to calculate the weights of the DMs based on the principle that the more accurate PHFE should be given a bigger weight. Then, the tail group decision making steps based on the EHVaR are presented. Finally, this paper provides an example of selecting the optimal stock for four newly listed stocks in China to demonstrate the effectiveness of the proposed approaches. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Hesitant VaR Expected hesitant VaR Probabilistic hesitant fuzzy element dynamic programming model Tail group decision making

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Static and dynamic resource allocation models for single-leg transportation markets with service disruptions

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2017年 103卷 87-108页

作者： Wang, Xinchang Mississippi State Univ Dept Mkt Quantitat Anal & Business Law Mississippi State MS 39762 USA

This work considers the stochastic resource allocation problem for single-leg transportation markets with service disruptions. The single-period version of the problem is formulated as a stochastic model with arbitrarily distributed resource capacity. We then completely characterize the optimal solution to the stochastic model. The multi-period version of the problem is formulated as a dynamic programming model. We characterize the monotone structure of the optimal solution for the dynamic model under uniform resource consumption rates. For the case with general resource consumption rates, a counterexample is provided to show that there exist cases where the optimal solution is not monotone. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Transportation markets Resource allocation Service disruptions dynamic programming model Uncertain capacity Monotone structure

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Study on the possibility degree of the optimal solution of grey dynamic programming model base on standard interval grey number

Study on the possibility degree of the optimal solution of g...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Shi, Hongxing Du, Hongyun Liu, Sifeng Xu, Chun Bengbu Coll Automobile Management Bengbu Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Econ Management Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781424427932

Considering the uncertainty of information, the paper puts forward an improved grey dynamic programming model. After that, treating profit value as positive interval grey number, the paper researches on dynamic programming model, and we could get the optimal strategy after solution by means of defining standard interval grey number. Furthermore, as we can not make the judgment of standard interval grey number, the author puts forward the possibility degree of the optimal solution, which represented as beta u(y) (k) is only related with f(i+1) (circle times)(S-i+1,S-k) and it has the features of 0 < beta u(ij) (k) < 1 and Sigma(t)(k=1) beta(uj) (k) = 1. Finally, the author verifies the practicability of the model by case study.

关键词： Grey Systems dynamic programming model Standard interval grey number Optimal solution Possibility degree

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modeling dependence among geologic risks in sequential exploration decisions

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SPE RESERVOIR EVALUATION & ENGINEERING 2008年第2期11卷 352-361页

作者： Bickel, J. Eric Smith, James E. Meyer, Jennifer L. Texas A&M Univ Dept Ind & Syst Engn College Stn TX 77843 USA Duke Univ Fuqua Sch Business Durham NC 27706 USA Strateg Decis Grp Palo Alto CA USA

Prospects in a common basin are likely to share geologic features. For example, if hydrocarbons are found at one location, they may be more likely to be found at other nearby locations. When making drilling decisions, we should be able to exploit this dependence and use drilling results from one location to make more informed decisions about other nearby prospects. Moreover, we should consider these informational synergies when evaluating multiprospect exploration opportunities. In this paper, we describe an approach for modeling the dependence among prospects and determining an optimal drilling strategy that takes this information into account. We demonstrate this approach using an example involving five prospects. This example demonstrates the value of modeling dependence and the value of learning about individual geologic risk factors (e.g., from doing a postmortem at a failed well) when choosing a drilling strategy.

关键词： Reservoir Characterization Upstream Oil & Gas Artificial Intelligence optimal strategy risk management dynamic programming model machine learning drilling operation information assessment Asset and Portfolio Management Decision-making processes Drilling Operations Project economics/valuation Reservoir Characterization Risk Management and Decision-Making

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Knowledge representation and rule-based solution system for dynamic programming model

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Journal of Harbin Institute of Technology(New Series) 2003年第2期10卷 190-194页

作者：胡祥培王旭茵 Institute of Systems Engineering

A knowledge representation has been proposed using the state space theory of Artificial Intelligence for dynamic programming model, in which a model can be defined as a six tuple M=(I,G,O,T,D,S). A building block modeling method uses the modules of a six tuple to form a rule based solution model. Moreover, a rule based system has been designed and set up to solve the dynamic programming model. This knowledge based representation can be easily used to express symbolical knowledge and dynamic characteristics for dynamic programming model, and the inference based on the knowledge in the process of solving dynamic programming model can also be conveniently realized in computer.

关键词： knowledge representation operations research dynamic programming model intelligent modeling support

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Optimal patch time allocation for time-limited foragers

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BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY 2006年第1期60卷 1-10页

作者： Wajnberg, E Bernhard, P Hamelin, F Boivin, G INRA Sophia Antipolis 06903 France Ecole Polytech Nice Sophia Antipolis CNRS UNSA I3S Sophia Antipolis 06903 France Agr & Agroalimentaire Canda Ctr Rech & Dev Hort St Jean PQ Canada

The Charnov Marginal Value Theorem (MVT) predicts the optimal foraging duration of animals exploiting patches of resources. The predictions of this model have been verified for various animal species. However, the model is based on several assumptions that are likely too simplistic. One of these assumptions is that animals are living forever (i.e., infinite horizon). Using a simple dynamic programming model, we tested the importance of this assumption by analysing the optimal strategy for time-limited foragers. We found that, for time-limited foragers, optimal patch residence times should be greater than those predicted from the classic, static MVT, and the deviation should increase when foragers are approaching the end of their life. These predictions were verified for females of the parasitoid Anaphes victus (Hymenoptera: Mymaridae) exploiting egg patches of its host, the carrot weevil Listronotus oregonensis (Coleoptera: Curculionidae). As predicted by the model, females indeed remained for a longer time on host patches when they approached the end of their life. Experimental results were finally analysed with a Cox regression model to identify the patch-leaving decision rules females used to behave according to the model's predictions.

关键词： Marginal Value Theorem time-limited foragers dynamic programming model Anaphes victus Cox regression model

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Factors affecting soldier allocation in clonal aphids: a life-history model and test

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BEHAVIORAL ECOLOGY 2004年第1期15卷 94-101页

作者： Tyerman, JG Roitberg, BD Univ British Columbia Dept Zool Vancouver BC V6T 1Z4 Canada Simon Fraser Univ Dept Biol Sci Behav Ecol Res Grp Burnaby BC V5A 1S6 Canada

Aphid species using a defensive soldier caste offer us the opportunity to study allocation decisions by eusocial groups, without the hindrance of genetic dissimilarity between colony members, which often impair studies involving Hymenopteran or Isopteran systems. When the entire aphid clone is considered the adaptive unit of organization, understanding soldier allocation strategies is tantamount to understanding the outcome of the tradeoff between clonal growth (i.e., asexual reproduction) and clonal defense. Under this framework, we present the results of a dynamic programming effort aimed at determining the optimal ontogeny of defensive allocation strategies by eusocial clonal organisms. We consider the allocation decision for clones with both obligately and facultatively sterile soldiers, under various levels of predation, and favorable and unfavorable ecological conditions. We test predictions of the model with the cusocial aphid, Pemphigus spyrothecae. Our model predicts that defensive investment should be dependent on the time of the season, with clones discounting defense nearer the end of season. Defensive investment should also vary inversely with clonal productivity and be sensitive to the current state (e.g., level of defense) of the clone. Census data collected in Burnaby, British Columbia, Canada, conform to patterns of clonal composition derived from allocation decisions generated in the model. Finally, qualitative predictions about patterns of clonal organization under "good" and "poor" ecological conditions were upheld by comparing clones in preferred and less-preferred galling sites.

关键词： colony defense dynamic programming model eusocial aphids Pemphigus spyrothecae soldier allocation strategies tradeoffs

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Analysis of energy demand and CO₂ emissions for the Indian aluminium industry using a dynamic programming model

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INTERNATIONAL JOURNAL OF ENERGY RESEARCH 2000年第1期24卷 51-59页

作者： Das, A Kandpal, TC Indira Gandhi Inst Dev Res Bombay 400065 Maharashtra India Indian Inst Technol Ctr Energy Studies New Delhi 110016 India

This paper presents a capacity planning model for the Indian aluminium industry based on a linear dynamic programming technique. The model has been used to analyse energy demand and CO2 emission for the period 1992-20... 详细信息

关键词： aluminium dynamic programming model energy demand CO2 emissions

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