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OPTIMAL PREPOSITIONING OF EMPTY FREIGHT CARS

SIMULATION 1984年第6期42卷 269-275页

作者： RATCLIFFE, LL VINOD, B SPARROW, FT RUTGERS STATE UNIV COLL ENGNDEPT IND ENGNPISCATAWAYNJ 08854 PURDUE UNIV SCH IND ENGNW LAFAYETTEIN 47907

The optimal utilization and distribution of empty freight cars has plagued the railroad industry in the past and will undoubt edly continue to do so in the future. In this paper we present the methodology for a simulation-optimization model, for the movement of empty freight cars in a hypothetical railroad transportation network. The freight car network is modelled in SLAM and integrated with XMP, a sophisticated and compact linear programming software package, to determine optimal movement and prepositioning of empty cars to the various nodes (terminals) in the network.

关键词： freight cars optimization prepositioning simulation stochastic linear programming transportation

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stochastic optimization methods in optimal engineering design under stochastic uncertainty

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ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND MECHANIK 2003年第12期83卷 795-811页

作者： Marti, K Fed Armed Forces Univ Munich Aerosp Engn & Technol D-85577 Munich Germany

Problems from optimal plastic design are based on the convex, linear or linearized yield/strength condition and the linear equilibrium equation for the generic stress (state) vector. Having to take into account, in practice, stochastic variations of the model parameters (e.g. yield stresses, plastic capacities) and external loadings, the basic stochastic optimal plastic design problem must be replaced by an appropriate deterministic substitute problem. After considering stochastic optimization methods based on failure/survival probabilities and presenting differentiation techniques and differentiation formulas for probability of failure/survival functions, a direct approach is presented using the construction and failure costs (e.g. costs for damage, repair, compensation for weakness within the structure, etc.). Based on the basic mechanical survival conditions, the failure costs may be represented by the minimum value of a convex and often linear program. Several mathematical properties of this program are shown. Minimizing then the total expected costs subject to the remaining (simple) deterministic constraints, a stochastic optimization problem is obtained which may be represented by a "stochastic Convex Program (SCP) with recourse". Working with linearized yield/strength conditions, a "stochastic linear Program (SLP) with complete fixed recourse" results. In case of a discretely distributed probability distribution or after the discretization of a more general probability distribution of the random structural parameters and loadings as well as certain random cost factors one has a linear program (LP) with a so-called "dual decomposition data" structure. For stochastic programs of this type many theoretical results and efficient numerical solution procedures (LP-solver) are available. The mathematical properties of theses substitute problems are considered, and numerical solution procedures are described. (C) 2003 WILEY-VCH Verlag GmbH & Co. KGaA. Weinheim.

关键词： optimal structural design limit load analysis stochastic uncertainty probability of failure expected costs of failure stochastic optimization stochastic linear programming

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Two-stage stochastic Assignment Problem in the Home Health Care

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IFAC-PapersOnLine 2016年第12期49卷 1152-1157页

作者： Errarhout, A. Kharraja, S. Corbier, C. Université de Lyon Saint EtienneF-42023 France Université de Saint Etienne Jean Monnet Saint EtienneF-42000 France LASPI IUT de Roanne F-42334 France

In this paper, we present a two-stage stochastic model for an assignment problem in the home health care structures. We search to assign nurses to patients during a planning horizon while considering the nurses’ skills and capacity. Furthermore, we take into account the randomness of the time required to give cares for patients (the nurse's time resource consumption during cares) as the uncertainty parameter in this problem. As aim, we balance the nurses’ workload, reduce their travel load and secure the continuity of the care. We present a two-stage stochastic linear programming model and the computational tests were done using CPLEX. © 2016

关键词： Home health care Combinatorial optimization linear programming Nursing stochastic models stochastic programming stochastic systems Assignment problems Continuity care Resource consumption stochastic linear programming Two stage stochastic models Two stage stochastic programming Uncertainty Uncertainty parameters

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Mean absolute negative deviation measure for portfolio selection problem

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JOURNAL OF INTERDISCIPLINARY MATHEMATICS 2010年第5期13卷 523-539页

作者： Kamil, Anton Abdulbasah Mustafa, Adli Ibrahim, Khlipah Univ Sains Malaysia Sch Distance Educ George Town 11800 Malaysia Univ Sains Malaysia Sch Math Sci George Town 11800 Malaysia

One of the important research areas in financial decision making is the optimization of portfolios. The uncertainty of the future returns of portfolios is an important character within this optimization problem. We utilized probabilistic methods together with optimization techniques to handle such problems. We developed two stage stochastic programming with recourse for risk-averse investors and the objective of the stochastic programming models is to minimize the mean absolute negative deviation of the portfolio returns from the expected portfolio returns. We used the so-called "Here-and-Now" approach where the decision-maker makes decision "now" in the first stage before observing the actual outcome in the second stage. We compared the optimal portfolios resulting from the two stage model that hedge against the risk of investment with the single stage mean absolute negative deviation model. These models were applied to the optimal selection of stocks listed in Bursa Malaysia and the returns of the optimal portfolio were compared. The results showed that the optimal portfolios from the two stage model out performed the optimal portfolios from the single stage model.

关键词： Portfolio optimization deviation measure mean absolute negative deviation stochastic linear programming

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On the stability of solutions under recursive programming

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Unternehmensforschung Operations Research - Recherche Opérationnelle 1966年第1期10卷 1-14页

作者： Sengupta, J.K. Tintner, G. Indian Institute of Management Calcutta India Department of Economics University of Southern California Los Angeles United States

Recursive linear programming is defined by a sequence of linear programming problems in which a recursive relation is built into the system through either the coefficients of the objective function, the constraint matrix, or the right-hand side parameters. Here we consider the case where the right-hand side parameters are subject to a recursive time relation indicating how current period plans are related to past expectations and performance. Our object here is twofold: first, to analyze the stability properties of a linear recursive programming (LRP) model and second, to indicate some basic extensions of the LRP in the light of what is generally called 'the active approach' of stochastic linear programming (SLP). Some simple theorems are developed in this connection and this is followed by a brief discussion of the possible lines of empirical applications. © 1966 Physica-Verlag.

关键词： Recursive Relation linear programming Problem Constraint Matrix stochastic linear programming Simple Theorem

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OPTIMIZING THE PROBABILITIES OF WATER YIELD FOR THE RIDAURA AQUIFER (SPAIN)

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JAWRA Journal of the American Water Resources Association 1992年第2期28卷 337-342页

作者： Trilla, J. Estalrich, J. Respectively Professor and Associate Professor Unidad de Geodinamica Externa e Hidrogeologia Dpto. Geologia Universidad Autonoma de Barcelona 08193 Bellaterrra Barcelona Spain.

ABSTRACT: Aquifer pumping represents, in many geographical locations, an alternative and/or a complementary source of water to surface water supplies. Several Catalonian coastal towns in the northeastern corner of Spain are in this situation. Also, since pumped water is used to supply drinking water, the main purpose in managing these water resources is to supply, no matter the cost, the amount needed at every moment. In other words, the managers of these aquifers attempt to optimize firm water yield. If we think of these aquifers as underground reservoirs with fixed storage capacity, most of the techniques which are applied to surface reservoirs can be implemented. In this paper we use a stochastic Dynamic programming model to optimize the yield from the aquifer of the Ridaura River. The objective function in this model was chosen with the aim of maximizing the reliability of the target yields in each of four seasons. Copyright © 1992, Wiley Blackwell. All rights reserved

关键词： aquifer management reliability stochastic dynamic programming stochastic linear programming

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Optimal Wind Bidding Strategies in Day-Ahead Markets 7th

Optimal Wind Bidding Strategies in Day-Ahead Markets

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7th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS)

作者： Gomes, Isaias L. R. Pousinho, Hugo M. I. Melicio, Rui Mendes, Victor M. F. Univ Lisbon Inst Super Tecn IDMEC LAETA Lisbon Portugal Univ Evora Escola Ciencias & Tecnol Dept Fis Evora Portugal Inst Super Engn Lisboa Lisbon Portugal

ISBN: (纸本)9783319311654;9783319311647

This paper presents a computer application (CoA) for wind energy (WEn) bidding strategies (BStr) in a pool-based electricity market (EMar) to better accommodate the variability of the renewable energy (ReEn) source. The CoA is based in a stochastic linear mathematical programming (SLPr) problem. The goal is to obtain the optimal wind bidding strategy (OWBS) so as to maximize the revenue (MRev). Electricity prices (EPr) and financial penalties (FiPen) for shortfall or surplus energy deliver are modeled. Finally, conclusions are addressed from a case study, using data from the pool-based EMar of the Iberian Peninsula.

关键词： Bidding strategies Wind power system stochastic linear programming Day-ahead market

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Configuration and Optimization of Virtual Business in Cloud Computing Environment

Configuration and Optimization of Virtual Business in Cloud ...

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2nd International Conference on Cloud and Green Computing / 2nd International Conference on Social Computing and its Applications (CGC/SCA)

作者： Sun, Hongjun Huang, Shuangxi Fan, Yushun Su, Wei China Aerosp Engn Consultat Ctr Beijing PR Peoples R China Tsinghua Univ Beijing Dept Automat Beijing Peoples R China

ISBN: (纸本)9780769548647;9781467330275

Cloud computing enables the realization of virtual business through outsourcing business functions to online services. Due to the large number of available business services and candidate cloud service providers, the configuration and optimization of the virtual business becomes a key issue for a service-oriented business ecosystem. In this paper, the virtual business is regarded as a series of service processes. Constrained service workflow net (CSWF-net) is developed to describe the component and structure of such service processes. Considering the dynamic and stochastic nature of services in a cloud computing environment, a stochastic decision making approach for CSWF-net is proposed in which the state transition of services is characterized as a Continuous Time Markov Chain (CTMC). Based on the four control structures of service processes, the dynamic Quality-of-Service (QoS) aware selection and composition problem is formulated as a stochastic linear programming (SLP) model. Mixed policies generated by the branch and bound algorithm and modified heuristic approach are used to solve the dynamic QoS-aware selection and composition problem at runtime. In the meantime, the most appropriate business services and cloud service providers can be selected to support the execution of the virtual business effectively.

关键词： Service processes service workflow net continuous time markov chain stochastic linear programming

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Modeling data integrity under stochastic linear constraints

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International Journal of Electronic Commerce Studies 2015年第2期6卷 233-242页

作者： Shing, Lee-Pin Shing, Lee-Hur Shing, Marn-Ling Shing, Chen-Chi Virginia Tech 926 Kabrich St Blacksburg 24060 VA United States Virginia Tech 1204 Highland Circle Blacksburg 24060 VA United States University of Taipei 1 Ai-Kuo West Road Taipei Taiwan Taiwan Radford University Radford University Box 6933 Radford 24142 VA United States

The most commonly used data integrity models today are Bibba, Wilson-Clark and Chinese models. These models are designed for both data integrity protection and confidentiality. Many optimization problems are related to linear programming. In practice, these variables involved are probabilistic. This paper proposes a data integrity model based on data anomalies assuming data are under stochastic linear constraints. An algorithm is constructed using the simplex method to find confidence intervals for the problem solutions. In the end the results from Monte Carlo simulation are compared with those from simplex method.

关键词： Data Integrity Model Risk Management Model stochastic linear programming

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Electricity and CO2 Emissions System Prices Modeling and Optimization

Electricity and CO2 Emissions System Prices Modeling and Opt...

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Bucharest PowerTech Conference

作者： Rebennack, Steffen Iliadis, Niko A. Pereira, Mario V. F. Pardalos, Panos M. Univ Florida Dept Ind & Syst Engn Gainesville FL 32611 USA EnerCoRD Athens 17121 Greece Ctr Empresarial Rio PSR BR-2225040 Rio De Janeiro RJ Brazil

ISBN: (纸本)9781424422340

We present two stochastic models optimizing a hydro-thermal power system;the first from the perspective of a global system and the second from a sub-system's (country or utility) perspective within a liberalized market. Particularly CO2 emission quotas and CO2 certificate prices are taken into account. The first model seeks to compute the electricity system marginal price as well as the CO2 emissions marginal price by minimizing the expected system's cost of operation. In the second model, the expected revenues of the sub-system within a liberalized electricity market while considering stochastic inflows, electricity, fuel and CO2 prices are maximized. The above-mentioned stochastic variables are represented via joint scenarios. The resulting stochastic linear program will be solved via hybrid SDP/SDDP.

关键词： CO2 portfolio management CO2 market price CO2 quota CO2 emission trading energy power systems optimization SDDP stochastic linear programming

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