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Optimal planning for container prestaging, discharging, and loading processes at seaport rail terminals with uncertainty

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2018年 119卷 88-109页

作者： Xie, Ying Song, Dong-Ping Anglia Ruskin Univ Lord Ashcroft Int Business Sch Bishop Hall Lane Chelmsford CM1 1SQ England Univ Liverpool Sch Management Chatham St Liverpool L69 7ZH Merseyside England

This paper considers the optimal planning problem for container prestaging and dynamic discharging/loading at seaport rail terminals subject to uncertainties. We formulate the problem into a stochastic dynamic programming model to minimise the total logistics cost. Four simplified strategies are proposed. Experiments based on a real case study are performed to compare the optimal strategy with four simplified strategies in terms of cost, computing time and practicality. Results show that the seaport can use prestaging to reduce the cost involved and that an appropriate discharging/loading plan can be created in response to different prestaging situations and uncertain scenarios.

关键词： Container transport Seaport rail terminal Prestaging Discharge and load stochastic dynamic programming

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Optimal power system expansion planning under uncertain CO2 emissions control policies

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ELECTRICAL ENGINEERING IN JAPAN 1996年第5期117卷 1-13页

作者： Fujii, Y Akimoto, K Yokohama National University [?]Completed his Ph.D. course in electrical engineering in 1993 at the Engineering Research Division of the Graduate School University of Tokyo. He has been an Assistant in the Department of Electronics and Information Engineering Yokohama National University since April of the same year. He is engaged in research on energy systems and discrete event systems. He is a member of the Energy and Resources Society as well as the Society of Instrument and Control Engineers.

Many efforts towards a settlement of the CO2 problem have already been made through internationally organized meetings. It is not unlikely that some targets will be set for the reduction of CO2 emissions. If a stringent reduction target should be imposed bn CO2 emitted from a national energy system, this can possibly have as severe an impact upon electric power sectors as the oil price crises experienced in the seventies. It is, however, quite uncertain whether or not political muscles will be used specifically for tackling the CO2 problem in the near future. In such a context, this paper presents a new method for optimal power system planning under uncertain CO2 emissions control policies. The derived optimal expansion plan gives us the minimum expected value of the sum of the total system cost and the total amount of carbon taxes levied on net CO2 emissions from fossil fuel-fired power plants. The stochastic dynamic optimization problem discussed here is formulated as a linear programming problem decomposable into several small subproblems. The proposed method can take into account a specific future scenario of the magnitude of control policy uncertainties, which can be presumably resolved in the first half of the next century due to the increase in scientific wisdom. In order to evaluate the usefulness of the method proposed here, the authors also present a simple case study with the Japanese national power system up to the year 2050.

关键词： CO2 problem optimal power system expansion planning uncertainty stochastic dynamic programming multistage decision problem

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Distribution of High-Definition Video in 802.11 Wireless Home Networks

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 2011年第1期57卷 53-61页

作者： Miguel, Victor Cabrera, Julian Jaureguizar, Fernando Garcia, Narciso Univ Politecn Madrid GTI E-28040 Madrid Spain

Wireless distribution of multimedia contents through 802.11 networks in the home environment presents a number of advantages which have fueled the interest of industry in recent years, such as simple connectivity and data delivery to a variety of devices. Together with High-Definition (HD) contents, multimedia wireless distribution has been proposed for several applications, such as IPTV and Digital TV distribution for multiple devices in the home environment. However, the quality of wireless multimedia services is deteriorated by random packet losses caused by the changing channel behavior. For these scenarios, we propose in this paper a multicast distribution system for High-Definition video over 802.11 wireless networks based on rate-limited packet retransmission. Unlike previous works, which require on-line calculation of the optimal retransmission strategies, the presented system employs optimal retransmission strategies obtained through an off-line optimization process. This approach, based on stochastic dynamic programming, allows a lower on-line complexity and, when compared to another limited rate ARQ system, offers a higher packet recovery and improvements in video quality for low end-to-end delays requirements(1).

关键词： HD multimedia distribution wireless home network stochastic dynamic programming ARQ

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Simultaneous control of production, preventive and corrective maintenance rates of a failure-prone manufacturing system

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APPLIED NUMERICAL MATHEMATICS 2008年第2期58卷 180-194页

作者： Kenne, J. P. Nkeungoue, L. J. Univ Quebec Ecole Technol Super Dept Engn Mech Lab Prod Technol Integrat Montreal PQ H3C 1K3 Canada

This paper deals with the control of corrective and preventive maintenance rates in the production planning of a manufacturing system with machines subject to random failures and repairs. The introduction of preventive and corrective maintenance will increase the availability of the production system which guarantees the improvement of the system's productivity if the production planning is well done. The objective of this study is to minimize a discounted overall cost consisting of maintenance cost, inventory holding and backlog cost. The decision variables are the production, the machine preventive and repair rates which influence the inventory levels and the system capacity respectively. In the proposed model. the failure rate of a machine depends on its age;hence, the corrective and preventive maintenance policies are machine-age dependent. A computational algorithm, based on numerical methods, is used for solving the optimal control problem. Finally, a numerical example and a sensitive analysis are presented to illustrate the usefulness of the proposed approach. The structure of the optimal control policy is presented and extensions to more complex manufacturing systems are discussed. (c) 2006 IMACS. Published by Elsevier B.V. All rights reserved.

关键词： corrective maintenance preventive maintenance production planning stochastic dynamic programming numerical methods

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Assessing hydropower operational profitability considering energy and reserve markets

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IET RENEWABLE POWER GENERATION 2017年第13期11卷 1640-1647页

作者： Helseth, Arild Fodstad, Marte Askeland, Magnus Mo, Birger Nilsen, Odd Bjarte Ignacio Perez-Diaz, Juan Chazarra, Manuel Guisandez, Ignacio SINTEF Energy Res Sem Saelands Vei 11 N-7465 Trondheim Norway Lyse Prod AS N-4069 Stavanger Norway Tech Univ Madrid UPM Dept Hydraul Energy & Environm Engn Madrid 28040 Spain

The authors analyse the operational profitability of a hydropower system selling both energy and reserve capacity in a competitive market setting. A mathematical model based on stochastic dynamic programming is used to compute the water values for the system considering different power plant configurations. The uncertainties in inflow and both energy and reserve capacity prices are considered through a discrete Markov chain. Subsequently, the system operation is simulated based on the obtained water values to assess system performance and expected revenues from the two markets. The model is applied in a case study for a Norwegian hydropower producer, showing how the power plant operation changes and profitability increases when considering sale of reserve capacity. The authors emphasise on how the water values are influenced by the opportunity to sell reserve capacity, and assess how the representation of non-convex relationships in the water value computations as well as simulation influence the profitability.

关键词： profitability power generation economics power markets hydroelectric power stations hydroelectric power stochastic programming dynamic programming pricing hydropower operational profitability assessment energy markets reserve markets energy capacity prices reserve capacity prices competitive market setting mathematical model stochastic dynamic programming water value computation power plant configurations Norwegian hydropower producer

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A new approach to modelling, control and simulation of knowledgeable manufacturing cell

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2007年第17期45卷 3779-3808页

作者： Yan, H. S. Dong, H. Southeast Univ Res Inst Automat Nanjing 210096 Peoples R China

The running of the knowledgeable manufacturing cell (KMC) is a typical discrete event dynamic process. Methods used to model and analyse discrete event dynamic systems (DEDS) include Petri net and automata theory. In this paper, a new matrix-automaton is proposed to model the KMC and solve the task control problems existing in the KMC. The automaton is of structured property and can be used to analyse the dynamic performance of the KMC. stochastic dynamic programming is used to derive the optimal task control strategy of the automaton, and a simulation method and program are proposed to simulate the running of the KMC. The matrix-automaton model of an experimental KMC including m manufacturing agents and n classes of workpieces is built and solved by the methods in this paper. Compared with the random control principle, the objective function value of the control strategy in this paper is obviously lower, which testifies the validity and feasibility of the control strategy.

关键词： knowledgeable manufacturing cell matrix-automaton stochastic dynamic programming control strategy simulation

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Rare breakthroughs vs. incremental development in R&D strategy for an early-stage energy technology

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ENERGY POLICY 2018年第Dec.期123卷 711-721页

作者： Fertig, Emily Carnegie Mellon Univ Dept Engn & Publ Policy 5000 Forbes Ave Pittsburgh PA 15213 USA

Uncertainty in technological learning is a crucial factor in planning research, development, and demonstration (RD&D) strategies. Nevertheless, most previous work either models technological change as deterministic or accounts for uncertainty without fully capturing the recourse feature of the problem. This paper improves upon these approaches by developing a real options-based stochastic dynamic programming method for valuing and planning low-carbon energy RD&D investment and is the first of its kind to disaggregate the effects of R&D and learning-by-doing. This simplified model captures the relevant features of the problem and provides general insights on RD&D strategy under technological uncertainty. Results indicate that imminent deployment, high cost, lower exogenous cost reductions, and lower program funds all promote R&D spending over learning-by doing, since under these circumstances a breakthrough, rather than slow and consistent cost reductions, will render the program successful.

关键词： Real options R&D stochastic dynamic programming Carbon capture and sequestration Managerial flexibility Endogenous technological change

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Opportunistic scheduling for a two-way relay network using Markov decision process

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IET COMMUNICATIONS 2016年第14期10卷 1846-1854页

作者： Meshgi, Hadi Zhao, Dongmei McMaster Univ Dept Elect & Comp Engn Hamilton ON Canada

In this study, the authors study transmission scheduling for a two-way relay network in time-varying fading channels, where the relay node can opportunistically use traditional one-way relay technique or network coding to forward traffic to the end nodes. They formulate a stochastic dynamic programme with the objective of minimising the long-run cost, defined as a function of both the transmission power and data transmission delay. An unconstrained Markov decision process model is developed and solved for the average and discounted cost problems. The optimal solution requires high computational and modelling complexity when the state space is large. For this reason, they develop heuristic solutions with lower complexity. For the discounted cost problem, a simulation-based dynamic programming algorithm is proposed that not only simplifies the modelling process and reduces the computational complexity, but also achieves close-to-optimum cost. For the average cost problem, a heuristic scheduling scheme is proposed, which makes transmission decisions based on estimated costs in the current and next time slots. The heuristic scheme achieves close-to-optimum cost performance while greatly reducing the computational complexity.

关键词： Markov processes decision theory telecommunication scheduling relay networks (telecommunication) time-varying channels fading channels minimisation stochastic programming dynamic programming computational complexity network coding telecommunication traffic opportunistic scheduling two-way relay network transmission scheduling time-varying fading channels relay node one-way relay technique network coding stochastic dynamic programming long-run cost minimization data transmission delay transmission power function unconstrained Markov decision process model discounted cost problems computational complexity modelling complexity simulation-based dynamic programming algorithm close-to-optimum cost heuristic scheduling scheme next time slots close-to-optimum cost performance average cost problems

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Optimal marketing of nursery crops from container-based production systems

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AMERICAN JOURNAL OF AGRICULTURAL ECONOMICS 1997年第1期79卷 235-245页

作者： Stokes, JR Mjelde, JW Hall, CR TEXAS A&M UNIV DEPT AGR ECONCOLLEGE STNTX 77843

Optimal production and marketing decisions for a nursery producing ornamental plants from a container-based production system are determined. The stochastic dynamic programming model developed captures the existence of a value-added, serial-stage production process with multiple products and intra- and interyear dynamics. Results suggest price differentials play an important role in determining the optimal size of plant to market. Further, federal taxes are important for determining the optimal production and marketing decisions while discounting and state taxes play minor roles. Analysis of the transition probability matrices associated with the optimal decisions indicate that the long-run behavior of the system can be generalized.

关键词： marketing nursery stochastic dynamic programming value-added taxes

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A Condition-Based Maintenance Model Including Resource Constraints on the Number of Inspections

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IEEE TRANSACTIONS ON RELIABILITY 2020年第3期69卷 1165-1176页

作者： Alvarez, Claudio Lopez-Campos, Monica Stegmaier, Raul Mancilla-David, Fernando Schurch, Roger Angulo, Alejandro Univ Tecn Federico Santa Maria Dept Ind Engn Valparaiso 1680 Chile Univ Colorado Dept Elect Engn Denver CO 80217 USA Univ Tecn Federico Santa Maria Dept Elect Engn Valparaiso 1680 Chile

This article presents a stochastic dynamic programming model for a condition-based maintenance application. The approach seeks to determine the most opportune moment to inspect and execute preventive maintenance over each component of a nonredundant system, where the number of inspections to be performed simultaneously during each period is limited due to resource constraints. The model minimizes the total maintenance cost per unit of time, considering failure, maintenance, and inspection costs. Unlike most related literature, the model proposed herein allows nonperiodic inspections;it does not require to predefine a maintenance threshold and does not necessarily connect inspections to maintenance actions. Also, the criticality of each component is not static through time, or defined beforehand, but dynamically determined according to the available resources and the risk of failure. A numerical example illustrates the performance of the proposed model in comparison to three traditional maintenance models, namely corrective maintenance, age-based maintenance, and condition-based maintenance with periodic inspections. Results suggest that the proposed model yields the best solution among the studied policies and is more efficient, with a significant reduction of 90% in inspection resources.

关键词： Inspection Degradation Numerical models Integrated circuit modeling stochastic processes Preventive maintenance Condition-based maintenance reliability resource constraints stochastic dynamic programming

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