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15th International Asian School-Seminar on Optimization Problems of Complex Systems (OPCS)

作者： Novikov, Artem Sobolev Inst Math Novosibirsk Russia

ISBN: (纸本)9781728129860

Retail is one of the largest industries for financial investments in Russia. There are various mathematical descriptions for the development of retail projects. Earlier in Ill the researchers considered the resource region development model and a corresponding linear stochastic programming problem, where the budget constraints are assumed to vary in a random manner at specified interval;and the methods of its solving. In this paper, we propose new models for planning retail investment projects related to carrying out promo efficiency in the retail chain. As well as in In these models are based on linear stochastic programming problems, where the dimension of the problems increases essentially, and the stochastic parameters appear in market behaviour. To solve this problem, we put forward the method based on its reduction to the deterministic one. For the numerical check of the algorithms we use the data on transactions of the LLC NSK Holdi.

关键词： modelling of the investment projects retail stochastic linear programming forecasting

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stochastic Optimization of Coordinated Wind-Photovoltaic Bids in Electricity Markets 17

Stochastic Optimization of Coordinated Wind-Photovoltaic Bid...

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17th IEEE International Power Electronics and Motion Control Conference (PEMC)

作者： Gomes, I. L. R. Pousinho, H. M. I. Melicio, R. Mendes, V. M. F. Univ Evora Univ Lisboa Escola Ciencias & Tecnol IDMECInst Super TecnDept Fis Evora Portugal Inst Super Engn Dept Elect Engn & Automat Lisbon Portugal Univ Evora Escola Ciencias & Tecnol Dept Fis Evora Portugal

ISBN: (纸本)9781509017980

This paper deals with the problem of coordinated operation of wind power with photovoltaic power in order to find optimal bid submission in a day-ahead electricity market. Uncertainty not only due to the electricity market price, but also due to wind and photovoltaic powers is handled in the context of a problem of stochastic linear programming. Additionally, the impact of the increase of the photovoltaic power capacity on the revenue is analysed, as well as the impact of reducing energy imbalance. A case study with data from the Iberian day-ahead electricity market is presented and a comparison between coordinated and uncoordinated operations is discussed.

关键词： coordinated bidding strategy stochastic linear programming day-ahead market Wind-PV power system

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Optimal Scheduling of Frequency Services Considering a Variable Largest-Power-Infeed-Loss

Optimal Scheduling of Frequency Services Considering a Varia...

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IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Badesa, Luis Teng, Fei Strbac, Goran Imperial Coll London Dept Elect & Elect Engn London SW7 2AZ England

ISBN: (纸本)9781538677032

Low levels of inertia due to increasing renewable penetration bring several challenges, such as the higher need for Primary Frequency Response (PFR). A potential solution to mitigate this problem consists on reducing the largest possible power loss in the grid. This paper develops a novel modelling framework to analyse the benefits of such approach. A new frequency-constrained stochastic Unit Commitment (SUC) is proposed here, which allows to dynamically reduce the largest possible loss in the optimisation problem. Furthermore, the effect of load damping is included by means of an approximation, while its effect is typically neglected in previous frequency-secured-UC studies. Through several case studies, we demonstrate that reducing the largest loss could significantly decrease operational cost and carbon emissions in the future Great Britain's grid.

关键词： Frequency services stochastic linear programming unit commitment wind energy

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Military inventory capacity and stock planning with surge and warning time and supplier constraints 21

Military inventory capacity and stock planning with surge an...

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21st International Congress on Modelling and Simulation (MODSIM) held jointly with the 23rd National Conference of the Australian-Society-for-Operations-Research / DSTO led Defence Operations Research Symposium (DORS

作者： Calbert, G. Thiagarajan, R. Rahman, M. Def Sci & Technol Grp Edinburgh Planning & Logist Decis Sci Branch Edinburgh SA 5111 Australia

ISBN: (纸本)9780987214355

linear programming has since its inception, always been strongly applied to inventory management. linear programming has also been used extensively in many military stockage problems. In a military context, two general events test and shape the supply chain. The first is the development of inventory control: stockholding and infrastructure capacity policies to meet demands associated with ongoing raise, train and sustain requirements. In this case, the military inventory policies have very similar characteristics to stockholding in a commercial supply chain, where demands are forecasted and corresponding procurement takes place. The second event that shapes the structure of the supply chain is the occurrence of a contingency demands, often termed a surge demand. In the second case, a contingency will have a planned demand, sustainment period and corresponding warning time. While the demand and sustainment period are critical to stockholding decisions, it is the warning time, which in conjunction with the vendors constraints on supplying at surge rates that is critical to developing inventory holdings, capacity and reserve stocks, often called war reserve materiel in the United States Department of Defence. One can often summarise the vendors constraints in supplying at a surge rate through the Contingency Provisioning Lead Time (CPLT), which is defined as that time the vendor can supply at the required contingency throughput rate. The CPLT may be greater than the warning time, indicating the vendor cannot supply at the required throughput rate at the start of the contingency. With the basic input parameters of raise, train and sustain demands;contingency demand;warning time;CPLT;and maximum order quantities;we form a linear program that optimises the infrastructure capacity, reserve stocks and nominal inventory holdings at a Defence logistics installation. This linear program is extended to include an "anytime" contingency, where the inventory constraints are formed

关键词： Inventory management military logistics linear programming stochastic linear programming

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Bendersova dekompozice v optimalizaci

Bendersova dekompozice v optimalizaci

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作者： Minaříková, Michaela Charles University of Prague

The Bachelor thesis is dealing with Benders decomposition in optimization, especially in stochastic linear programming. In the begining the reader will be introduced to the important terms used in the decomposition algorithm. Con- sequently it is demonstrated how to reformulate the problem of stochastic linear programming to a special structure suitable for Benders decomposition. In the third chapter, the decomposition algorithm, using the feasibility and optimality cuts, is explained including conditions of convergence of the algorithm. There follows modification of algorithm for two stage stochastic linear programming. Finally, we illustrate Benders algorithm on two smaller problems. 1

关键词： Benders decomposition stochastic linear programming feasibility cut optimality cut

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Container fleet renewal considering multiple sulfur reduction technologies and uncertain markets amidst COVID-19

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JOURNAL OF CLEANER PRODUCTION 2021年 317卷 128361-128361页

作者： Zhao, Yuzhe Ye, Jiajun Zhou, Jingmiao Dalian Maritime Univ Collaborat Innovat Ctr Transport Studies Dalian Peoples R China Dalian Univ Foreign Languages Business Sch Dalian Peoples R China

The onset of 2020 is marked by stricter restrictions on maritime sulfur emissions and the spread of Coronavirus Disease 2019 (COVID-19). In this background, liner companies now face the challenge to find suitable sulfur reduction technologies, make reasonable decisions on fleet renewal, and prepare stable operation plans under the highly uncertain shipping market. Considering three sulfur reduction technologies, namely, fuel-switching, scrubber, and liquefied natural gas (LNG) dual-fuel engine, this paper develops a robust optimization model based on two-stage stochastic linear programming (SLP) to formulate a decision plan for container fleet, which can deal with various uncertainties in future: freight demand, ship charter rate, fuel price, retrofit time and Sulfur Emission Control Area (SECA) ratio. The main decision contents include ship acquisition, ship retrofit, ship sale, ship charter, route assignment, and speed optimization. The effectiveness of our plan was verified through a case study on two liner routes from the Far East to Northwest America, operated by COSCO Shipping Lines. The results from SLP model show that large-capacity fuel-switching ships and their LNG dual-fuel engine retrofits should be included in the long-term investment and operation plan;slow-steaming is an important operational decision for ocean liner shipping;if the current SECA boundary is not further expanded or the sulfur emission restrictions not further tightened, the scrubber ship will have no advantage in investment cost and operation. However, considering the probabilities of more flexible scenarios, the results from the robust model suggest that it is beneficial to install scrubber on medium-capacity fuel-switching ships, and carry out more LNG dual-fuel engine retrofits for large-capacity fuel-switching ships. Compared with SLP, this robust strategy greatly reduces sulfur emissions while slightly pushing up carbon emissions.

关键词： Maritime fleet renewal problem (MFRP) Sulfur reduction technologies stochastic linear programming Robust optimization Sulfur emission control area (SECA)

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Scenario Based Global Supply Chain Planning Process Considering Demand Uncertainty

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Journal of International Logistics and Trade 2013年第1期11卷 67-86页

作者： Hongjoo Lee Hosang Jung

In this paper, we propose a scenario based global supply chain planning (GSCP) process considering demand uncertainty originated from various global supply chain risks. To generate the global supply chain plan, we first formulate a GSCP model. Then, we need to generate several scenarios which can represent various demand uncertainties. Lastly, a planning procedure for considering those defined scenarios is applied. Unlike the past related researches, we adopt the fuzzy set theory to represent the demand scenarios. Also, a scenario voting process is added to calculate a probability (possibility) of each scenario. An illustrative example based on a real world case is presented to show the feasibility of the proposed planning process.

关键词： Global supply chain planning Demand uncertainty Scenario Fuzzy set theory stochastic linear programming

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Benders decomposition with special purpose method for the sub problem in lot sizing problem under uncertain demand

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OPERATIONS RESEARCH PERSPECTIVES 2019年 6卷

作者： Witthayapraphakorn, Aphisak Charnsethikul, Peerayuth Kasetsart Univ Ind Engn Dept 50 Ngam Wong Wan Rd Bangkok 10900 Thailand

We propose herein the application of Benders decomposition with stochastic linear programming instead of the mix integer linear programming (MILP) approach to solve a lot sizing problem under uncertain demand, particularly in the case of a large-scale problem involving a large number of simulated scenarios. In addition, a special purpose method is introduced to solve the sub problem of Benders decomposition and reduce the processing time. Our experiments show that Benders decomposition combined with the special purpose method (BCS) requires shorter processing times compared to the simple MILP approach in the case of large-scale problems. Furthermore, our BCS approach shows a linear relationship between the processing time and the number of scenarios, whereas the MILP approach shows a quadratic relationship between those variables, indicating that our approach is suitable in solving such problems.

关键词： Benders decomposition stochastic linear programming Large-scale problem Lot sizing problem Uncertain demand

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Analytical Solution of stochastic Load Flows in Network Planning

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IFAC Proceedings Volumes 1985年第7期18卷 381-384页

作者： E. López P. C. Fernández M. E. Salazar H. Department of Electrical Engineering Universidad de Concepción Casilla 53-C Concepción Chile Department of Mathematics Universidad de Concepción Casilla 2017 Concepción Chile

This paper presents a linear model for stochastic load flows (S. L. F.) studies in electric power systems when the effect of unit commitment is taken into account. It propose a method which permit to obtain the exact analytical solution of the random vector of powers generated by the production units (and thus, the load flow solution and the probability of lines overload) and some statistical indices of interest. In order to consider explicitly the production units a connection matrix is used. It allows us to consider the non-identica1 production units to be linked to the same node. The proposed model is especially well adapted for network planning studies. For this special application an algorithm is suggested.

关键词： Electric power systems models in network planning power transmission probability stochastic linear programming stochastic load flows

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

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WATER RESOURCES BULLETIN 1992年第2期28卷 337-342页

作者： TRILLA, J ESTALRICH, J Univ Autonoma de Barcelona Barcelona Spain

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.

关键词： stochastic DYNAMIC programming stochastic linear programming AQUIFER MANAGEMENT RELIABILITY

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