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Searching for an optimal rotation age for forest stand management under stochastic log prices

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1998年第1期105卷 100-112页

作者： Yoshimoto, A Shoji, I Miyazaki Univ Dept Agr & Forest Econ Miyazaki 88921 Japan Univ Tsukuba Inst Policy & Planning Sci Ibaraki Osaka 305 Japan

Due to rapid change in timber prices in the Japanese market most likely affected by imported timber from countries such as the U.S., Canada, and the Nordic countries, the domestic forest managers have been facing a large degree of future price uncertainty. Because of this, it becomes necessary to take the future price uncertainty into account within the forest management framework. In this paper, the continuous time stochastic process, i.e., the geometric Brownian motion, has been used to model the log price process. The binomial option pricing approximation was then applied to value the Sugi (Cryptomeria japonica) and Hinoki (Chamaecyparis obtusa) forested land under stochastic log prices in order to search for an optimal rotation age. Our experiments with the proposed two state stochastic dynamic programming model showed that when the current log price is high enough to cover all costs, an optimal rotation age from the stochastic price and deterministic price models coincides, although the total expected present net value from management activities differs. Also it was shown that as the current log price decreases, an optimal rotation age derived from the stochastic price model becomes longer than that from the deterministic price model. If the current log price further decreases, then forest management will be abandoned, and the forest stand will be converted into alternative uses. (C) 1998 Elsevier Science B.V.

关键词： agriculture forest economics stochastic differential equation stochastic dynamic programming

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Determining the optimal direct mailing frequency

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2004年第1期158卷 173-182页

作者： Piersma, N Jonker, JJ HES Amsterdam Amsterdam Sch Business NL-1000 AG Amsterdam Netherlands Erasmus Univ Inst Econometr NL-3000 DR Rotterdam Netherlands Social & Cultural Planning Off NL-2500 BD The Hague Netherlands

This paper studies the mailing frequency problem that addresses the issue of how often to send a mailing to an individual customer in order to establish a profitable long-term relation rather than targeting profitable groups of customers at every new mailing instance. The mailing frequency is optimized using long-term objectives but restricts the decisions to the number of mailings to send to the individual over consecutive finite planning periods. A stochastic dynamic programming model is formulated for this problem that can easily be applied to various direct marketing frameworks such as catalog sales or charity organizations. The model is calibrated for a large Dutch non-profit organization and shows that substantial improvements can be achieved by approaching the mailing strategy with the mailing frequency problem, both in the number of mailings to send and in the profits resulting from the responses. (C) 2003 Elsevier B.V. All rights reserved.

关键词： direct marketing stochastic dynamic programming

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stochastic dynamic Pricing for EV Charging Stations With Renewable Integration and Energy Storage

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IEEE TRANSACTIONS ON SMART GRID 2018年第2期9卷 1494-1505页

作者： Luo, Chao Huang, Yih-Fang Gupta, Vijay Univ Notre Dame Dept Elect Engn Notre Dame IN 46556 USA

This paper studies the problem of stochastic dynamic pricing and energy management policy for electric vehicle (EV) charging service providers. In the presence of renewable energy integration and energy storage system, EV charging service providers must deal with multiple uncertainties-charging demand volatility, inherent intermittency of renewable energy generation, and wholesale electricity price fluctuation. The motivation behind our work is to offer guidelines for charging service providers to determine proper charging prices and manage electricity to balance the competing objectives of improving profitability, enhancing customer satisfaction, and reducing impact on power grid in spite of these uncertainties. We propose a new metric to assess the impact on power grid without solving complete power flow equations. To protect service providers from severe financial losses, a safeguard of profit is incorporated in the model. Two algorithms-stochastic dynamic programming (SDP) algorithm and greedy algorithm (benchmark algorithm)-are applied to derive the pricing and electricity procurement policy. A Pareto front of the multi-objective optimization is derived. Simulation results show that using SDP algorithm can achieve up to 7% profit gain over using greedy algorithm. Additionally, we observe that the charging service provider is able to reshape spatial-temporal charging demands to reduce the impact on power grid via pricing signals.

关键词： Electric vehicle charging station dynamic pricing energy management renewable energy energy storage multi-objective optimization stochastic dynamic programming

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OPTIMAL CONTROL POLICIES FOR AN M/M/1 QUEUE WITH A REMOVABLE SERVER AND dynamic SERVICE RATES

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PROBABILITY IN THE ENGINEERING AND INFORMATIONAL SCIENCES 2021年第2期35卷 189-209页

作者： Badian-Pessot, Pamela Lewis, Mark E. Down, Douglas G. Cornell Univ Sch Operat Res & Informat Engn Ithaca NY 14850 USA McMaster Univ Dept Comp & Software Hamilton ON Canada

We consider an M/M/1 queue with a removable server that dynamically chooses its service rate from a set of finitely many rates. If the server is off, the system must warm up for a random, exponentially distributed amount of time, before it can begin processing jobs. We show under the average cost criterion, that work conserving policies are optimal. We then demonstrate the optimal policy can be characterized by a threshold for turning on the server and the optimal service rate increases monotonically with the number in system. Finally, we present some numerical experiments to provide insights into the practicality of having both a removable server and service rate control.

关键词： applied probability queueing theory stochastic dynamic programming

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Linear quadratic dynamic programming for water reservoir management

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APPLIED MATHEMATICAL MODELLING 1997年第9期21卷 591-598页

作者： Ozelkan, EC Galambosi, A FernandezGaucherand, E Duckstein, L Systems and Industrial Engineering Department University of Arizona Tucson AZ USA

dynamic programming (DP) is applied in order to determine the optimal management policy for a water reservoir by modeling the physical problem via a linear quadratic (LQ) structure. A simplified solution to the LQ tracking problem ir provided under mild assumptions. The model presents an aggregated multicriteria decision making problem where flood control, hydroelectric power, and water demand have to be satisfied Simultaneously the energy production ir to be maximized the mismatch of water demand minimized and the water release should not cause flooding. The system constraints are basically the conservation of mass within the reservoir system, and the minimum and the maximum allowable limits for the water release and the reservoir level. The stochastic variables consist of the water inflow from the reservoir drainage basin, precipitation and evaporation. The Tenkiller Ferry dam on the Illinois River basin in Oklahoma is analyzed as a case study. (C) 1997 by Elsevier Science Inc.

关键词： stochastic dynamic programming linear quadratic tracking reservoir management

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Selection of contract suppliers under price and demand uncertainty in a dynamic market

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2009年第3期198卷 830-847页

作者： Li, Shanling Murat, Alper Huang, Wanzhen Wayne State Univ Dept Ind & Mfg Engn Detroit MI 48202 USA McGill Univ Fac Management Montreal PQ H3A 1G5 Canada Lakehead Univ Dept Math Sci Thunder Bay ON P7B 5E1 Canada

In this paper, we consider a supply contracting problem in which the buyer firm faces non-stationary stochastic price and demand. First, we derive analytical results to compare two pure strategies: (i) periodically purchasing from the spot market;and (ii) signing a long-term contract with a single supplier. The results from the pure strategies show that the selection of suppliers can be complicated by many parameters, and is particularly affected by price uncertainty. We then develop a stochastic dynamic programming model to incorporate mixed strategies, purchasing commitments and contract cancellations. Computational results show that increases in price (demand) uncertainty favor long-term (short-term) suppliers. By examining the two-way interactions of contract factors (price, demand, purchasing bounds, learning and technology effect, salvage values and contract cancellation), both intuitive and non-intuitive managerial insights in outsourcing strategies are derived. (C) 2008 Published by Elsevier B.V.

关键词： Supply chain contracts stochastic dynamic programming Purchasing Supplier selection

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dynamic hedging in incomplete markets using risk measures

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IMA JOURNAL OF MANAGEMENT MATHEMATICS 2022年第2期33卷 345-367页

作者： Gaillardetz, Patrice Hachem, Saeb Concordia Univ Dept Math & Stat Montreal PQ H3G 1M8 Canada

In this paper, we consider the pricing of financial derivatives that involve dynamic hedging strategies and payments within the planning horizon. Equity-indexed annuities (EIAs), guaranteed investment certificates (GICs) and American and barrier options are typical examples of these products. Our exploration involves the use and comparison of alternative models that use risk measures. Although the hedging is done for each observation of the input stochastic process, the appropriate mix of risk measures and state dynamic equations helps the issuer to appropriately tailor the overall risk exercise. These different models are solved by a unified backward stochastic dynamic programming framework that we imbed with parametric techniques to shorten the running time and manage the curse of dimensionality in dynamic programming. To demonstrate the flexibility of this framework we present numerical examples featuring GICs and point-to-point EIAs. Finally, by using sampling techniques, optimal hedging strategies and specific indicators of the hedging performance, we make recommendations on how to fine tune the risk measure parameters.

关键词： partial hedging local risk-minimizing strategies stochastic dynamic programming linear programming parametric linear programming risk measures

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Climate resilience and profitability thresholds in Chesapeake Bay oyster aquaculture

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024年 372卷 123202页

作者： Weber, Matt A. Wainger, Lisa A. Testa, Jeremy M. Waldbusser, George G. Li, Ming Univ Maryland Ctr Environm Sci Chesapeake Biol Lab Solomons MD 20688 USA Oregon State Univ Coll Earth Ocean & Atmospher Sci Corvallis OR USA Univ Maryland Ctr Environm Sci Horn Point Lab Cambridge MD USA

Shellfish aquaculture producers in coastal systems are facing uncertain future growing conditions as climate change alters weather patterns and raises sea level. We examined expected mid-century (2059-2068) changes in aquaculture profitability from recent conditions by integrating models of climate change, estuarine hydrodynamics and biogeochemistry, oyster growth, oyster mortality, and economics, using the Chesapeake Bay, USA as a case study. We developed an economic stochastic dynamic programming (SDP) approach that generates optimal grower behavior to maximize profits under uncertainty by dynamically choosing planting density, replanting and mitigation use, in response to changing oyster stock status and water quality conditions. Separate models were developed for bottom culture largely serving the cannery market, and container culture largely serving the half-shell market, to reflect different production costs, market prices, and oyster growth and survival. The coupled hydrodynamic-biogeochemical and oyster ecology models projected high spatial variability in oyster growth and mortality with the most favorable growing conditions in the lower north and upper mid bay, where mortality is lowest, and the upper south bay, where growth is highest. Climate change by late mid-century generated modest water quality changes and virtually no mortality rate changes. Nonetheless, our modeling revealed that even if growers made optimal management choices under uncertainty, the majority of modeled sites would see a decline in profitability under climate change, primarily due to potential reductions in food availability. Bottom culture was more resilient to the future climate at most sites, being less sensitive to small changes in growth than container culture. Information on how aquaculture conditions currently vary in space was more important for profitability than future climate forecasts. Our stochastic dynamic programming approach tailored grower behavior to each site and

关键词： Oyster aquaculture Chesapeake bay Climate change Mitigation stochastic dynamic programming

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Optimal control of Atlantic population Canada geese

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ECOLOGICAL MODELLING 2007年第1期201卷 27-36页

作者： Hauser, C. E. Runge, M. C. Cooch, E. G. Johnson, F. A. Harvey, W. F. Univ Queensland Dept Math St Lucia Qld 4072 Australia USGS Patuxent Wildlife Res Ctr Laurel MD 20708 USA Cornell Univ Dept Nat Resources Ithaca NY 14853 USA US Fish & Wildlife Serv Gainesville FL 32611 USA Maryland Dept Nat Resources Wye Mills MD 21679 USA

Management of Canada geese (Branta canadensis) can be a balance between providing sustained harvest opportunity while not allowing populations to become overabundant and cause damage. in this paper, we focus on the Atlantic population of Canada geese and use stochastic dynamic programming to determine the optimal harvest strategy over a range of plausible models for population dynamics. There is evidence to suggest that the population exhibits significant age structure, and it is possible to reconstruct age structure from surveys. Consequently the harvest strategy is a function of the age composition, as well as the abundance, of the population. The objective is to maximize harvest while maintaining the number of breeding adults in the population between specified upper and lower limits. In addition, the total harvest capacity is limited and there is uncertainty about the strength of density-dependence. We find that under a density-independent model, harvest is maximized by maintaining the breeding population at the highest acceptable abundance. However if harvest capacity is limited, then the optimal long-term breeding population size is lower than the highest acceptable level, to reduce the risk of the population growing to an unacceptably large size. Under the proposed density-dependent model, harvest is maximized by maintaining the breeding population at an intermediate level between the bounds on acceptable population size;limits to harvest capacity have little effect on the optimal long-term population size. It is clear that the strength of density-dependence and constraints on harvest significantly affect the optimal harvest strategy for this population. Model discrimination might be achieved in the long term, while continuing to meet management goals, by adopting an adaptive management strategy. (c) 2006 Elsevier B.V. All rights reserved.

关键词： stochastic dynamic programming harvest control Canada geese Branta canadensis uncertainty age structure

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The impacts of uncertainties on the carbon mitigation design: Perspective from abatement cost and emission rate

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JOURNAL OF CLEANER PRODUCTION 2019年 232卷 213-223页

作者： Guo, Jian-Xin Tan, Xianchun Gu, Baihe Qu, Xinglong Chinese Acad Sci Inst Sci & Dev Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100190 Peoples R China Hangzhou Dianzi Univ Res Ctr Informat Technol & Social & Econ Dev Hangzhou 310018 Zhejiang Peoples R China Chinese Acad Sci Acad Math & Syst Sci Beijing 100190 Peoples R China

In this paper, we use a stochastic dynamic programming model to evaluate the impacts of uncertainties on the abatement planning process. By involving the endogenous emission path, we differentiate two types of uncertainties during the planning process, which come from the volatility of the abatement cost and the ambiguity of emission rate. Results suggest that the considered uncertainties influence the decision-making process in several aspects by shaping the abatement path as well as emission path. (1) The impacts vary with the expected value and the level of variance of the uncertainty effects. Uncertainties caused by abatement costs from 0.02 to 0.06 and emission factors from 0.01 to 0.03 increase the total abatement costs around 7% and 5% respectively. (2) Both of these uncertainties can generate precautionary abatement in short-term. Especially during the early stages, the abatement task will be increased by 1% around in each period due to the uncertainties. However such an action will be diminishing as the duration elapses. (3) Both of these uncertainties influence the long-term abatement performances, however, with different forms and mechanisms. With small volatility, the emission rate changes the priority sequence of abatement actions more substantially in the short-term than the emission rate does. (4) The combined uncertainties can behave in a compound way to improve the uncertainty performance in the model. The difference between the emission peaks of conservative and extreme cases is significant with the gap being about 5 million metric ton. These results have potentially important policy implications and can provide a rationale for abatement actions. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Climate change mitigation Abatement strategy Abatement uncertainty stochastic dynamic programming

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