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Modelling medical oxygen supply chain network under demand uncertainty using stochastic programming

OPSEARCH 2024年第4期61卷 2158-2190页

作者： Sawant, Rahul Kumar, Anish Yadav, Vineet Kumar Natl Inst Technol Dept Prod Engn Tiruchirappalli 620015 Tamil Nadu India OP Jindal Global Univ Jindal Global Business Sch Sonipat 131001 Haryana India

Supply chains are becoming more and more uncertain. It is more relevant now than ever to plan and model supply chains to handle such uncertainties. This paper designs a supply chain network for medical oxygen under uncertain demand. The paper tackles the complex logistical challenge of managing emergency medical supplies of medical-grade oxygen in the scenario of a pandemic. A facility location problem considering scenario-based uncertain demand is formulated using two-stage stochastic programming. An inventory distribution problem is next formulated to model the flow of medical oxygen in multiple periods to provide maximum service to medical facilities when the available transportation capacity is finite. The model includes various aspects that reflect the scenarios originating in a pandemic, such as limited vehicle availability, limited production capability, uncertain demand, etc. A scenario-based stochastic approach is considered to include the uncertainty aspect of a pandemic scenario. The proposed methodology was studied using two numerical analyses. The results show that, as the number of cryogenic vehicles available was finite, having buffer facilities such as cryogenic tanks to store liquid oxygen helps absorb demand variations in a pandemic scenario. A greater number of medical facilities can be serviced with fewer storage facilities, which can be very crucial in a pandemic scenario. Considering the need for swift planning required in emergency scenarios, the results will be useful for managers, practitioners, and academicians to make supply chains more resilient to risks and uncertainties.

关键词： Supply chain network Facility location stochastic programming Demand uncertainty Operational planning

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stochastic programming to evaluate the benefits of coordination mechanisms in the forest supply chain

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COMPUTERS & INDUSTRIAL ENGINEERING 2023年 184卷

作者： Simard, Vanessa Ronnqvist, Mikael Lebel, Luc Lehoux, Nadia Univ Laval Mech Engn Dept Quebec City PQ Canada Univ Laval Dept Wood & Forest Sci Quebec City PQ Canada Univ Laval 1065 Av MedLocal 1504 Quebec City PQ G1V 0A6 Canada

In natural resource sectors such as forestry, supply is subject to yield uncertainty, which can make planning decisions a challenge. A common way of dealing with uncertainty is to coordinate the decisions so all units in a network can better prepare for unpredicted events. This can generate plans that are more robust and reduce the negative impacts of uncertainty. The objective of this study is to evaluate the benefits of including coordination mechanisms in a forest supply chain to better face yield uncertainty. First, a stochastic program is developed to simulate a sawmill production planning decision process, taking wood supply uncertainty into account. Based on this model, six coordination mechanisms are proposed to help reduce the impact of an uncertain wood supply. The impact of uncertainty is measured using the individual transportation cost of each sawmill, the overall network cost, the cost for replanning operations, the volume of extra resources needed, backorders, and the prescribed wood supply from forest sites to sawmills. Historical data from a partnering company in the province of Quebec, Canada, are used to quantify the current level of uncertainty. Compared to the typical strategy of Fixed Supply and Fixed Demand, the Free Supply with Free Demand mechanism generates plans with more stability, offering a 64% reduction in transportation cost, and a reduction of 84 % in the volume of extra resources to be acquired outside the regular sources at a higher cost to prevent production shortage.

关键词： Coordination mechanisms Forest supply chain stochastic programming Uncertain supply

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stochastic programming of energy system operations considering terminal energy storage levels

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COMPUTERS & CHEMICAL ENGINEERING 2023年 179卷

作者： Ikonen, Teemu J. Han, Dongho Lee, Jay H. Harjunkoski, Iiro Aalto Univ Dept Chem & Met Engn POB 16100 Aalto 00076 Finland Korea Adv Inst Sci & Technol Dept Chem & Biomol Engn 291 Daehak Ro Daejeon 305701 South Korea Univ Southern Calif Mork Family Dept Chem Engn & Mat Sci Main Dept Aerosp & Mech Engn Joint VHE3103651 Watt Way Los Angeles CA 90089 USA Hitachi Energy Res Havellandstr 10-14 D-68309 Mannheim Germany

Energy storage units offer vital balancing power for energy systems with an increasing amount of variable renewable energy (VRE) sources. The operation of such systems can be optimized by stochastic programming, which anticipates the uncertainty related to the variable renewable energy sources. However, these optimization problems can only be formulated for optimization horizons with a finite length, due to the rapidly increasing problem size and uncertainty in VRE production. Realistic valuation of the stored energy at the end of a horizon is important for long-term operation of the system. In this work, we investigate two different valuation methods, which are based on forecasted electricity prices, for storage-only and producer-oriented energy systems that participate in the day-ahead market. On a case study on the German day-ahead market, the methods yield competitive profits with reduced cycling of the energy storage unit and deviations with respect to the day-ahead trading.

关键词： Energy storage stochastic programming Day-ahead market Renewable energy Photovoltaic power

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Coupled Learning Enabled stochastic programming with Endogenous Uncertainty

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MATHEMATICS OF OPERATIONS RESEARCH 2022年第2期47卷 1681-1705页

作者： Liu, Junyi Li, Guangyu Sen, Suvrajeet Tsinghua Univ Dept Ind Engn Beijing 100084 Peoples R China Univ Southern Calif Dept Elect & Comp Engn Los Angeles CA 90089 USA Univ Southern Calif Dept Ind & Syst Engn Los Angeles CA 90089 USA

Predictive analytics, empowered by machine learning, is usually followed by decision-making problems in prescriptive analytics. We extend the previous sequential prediction-optimization paradigm to a coupled scheme such that the prediction model can guide the decision problem to produce coordinated decisions yielding higher levels of performance. Specifically, for stochastic programming (SP) models with latently decision-dependent uncertainty, without any parametric assumption of the latent dependency, we develop a coupled learning enabled optimization (CLEO) algorithm in which the learning step of predicting the local dependency and the optimization step of computing a candidate decision are conducted interactively. The CLEO algorithm automatically balances the exploration and exploitation via the trust region method with active sampling. Under certain assumptions, we show that the sequence of solutions provided by CLEO converges to a directional stationary point of the original nonconvex and nonsmooth SP problem with probability 1. In addition, we present preliminary experimental results which demonstrate the computational potential of this data-driven approach.

关键词： stochastic programming endogenous uncertainty trust region method local linear regression

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stochastic programming approach for optimal day-ahead market bidding curves of a microgrid

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APPLIED ENERGY 2023年 336卷

作者： Herding, Robert Ross, Emma Jones, Wayne R. Charitopoulos, Vassilis M. Papageorgiou, Lazaros G. UCL Univ Coll London Sargent Ctr Proc Syst Engn Dept Chem Engn Torrington Pl London WC1E 7JE England Global Solut Int BV NL-1031 HW Amsterdam Netherlands Shell plc Shell Ctr London SE1 7NA England

The deregulation of electricity markets has driven the need to optimise market bidding strategies, e.g. when and how much electricity to buy or sell, in order to gain an economic advantage in a competitive market environment. The present work aims to determine optimal day-ahead market bidding curves for a microgrid comprised of a battery, power generator, photovoltaic (PV) system and an electricity load from a commercial building. Existing day-ahead market bidding models heuristically fix price values for each allowed bidding curve point prior to the optimisation problem or relax limitations set by market rules on the number of price-quantity points per curve. In contrast, this work integrates the optimal selection of prices for the construction of day-ahead market bidding curves into the optimisation of the energy system schedule;aiming to further enhance the bidding curve accuracy while remaining feasible under present market rules. The examined optimisation problem is formulated as a mixed integer linear programming (MILP) model, embedded in a two-stage stochastic programming approach. Uncertainty is considered in the electricity price and the PV power. First stage decisions are day-ahead market bidding curves, while the overall objective is to minimise the expected operational cost of the microgrid. The bidding strategy derived is then examined through Monte Carlo simulations by comparing it against a deterministic approach and two alternative stochastic bidding approaches from literature.

关键词： Mixed-integer linear programming stochastic programming Optimisation under uncertainty Microgrid Bidding curve Day-ahead market

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Risk-Averse stochastic programming: Time Consistency and Optimal Stopping

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OPERATIONS RESEARCH 2022年第4期70卷 2439-2455页

作者： Pichler, Alois Liu, Rui Peng Shapiro, Alexander Tech Univ Chemnitz Fak Math D-09111 Chemnitz Germany Georgia Inst Technol Sch Ind & Syst Engn Atlanta GA 30332 USA

This paper addresses time consistency of risk-averse optimal stopping in stochastic optimization. It is demonstrated that time-consistent optimal stopping entails a specific structure of the functionals describing the transition between consecutive stages. The stopping risk measures capture this structural behavior and allow natural dynamic equations for risk-averse decision making over time. Consequently, associated optimal policies satisfy Bellman's principle of optimality, which characterizes optimal policies for optimization by stating that a decision maker should not reconsider previous decisions retrospectively. We also discuss numerical approaches to solving such problems.

关键词： stochastic programming coherent risk measures time consistency dynamic equations optimal stopping time Snell envelope inventory model American put option

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A stochastic programming model for the aircraft sequencing and scheduling problem considering flight duration uncertainties

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AERONAUTICAL JOURNAL 2022年第1304期126卷 1736-1751页

作者： Cecen, R. K. Eskisehir Osmangazi Univ Eskisehir Turkey

This study presents a stochastic mixed-integer linear programming model for the aircraft sequencing and scheduling problem. The proposed model aims to minimise the average fuel consumption per aircraft in the Terminal Manoeuvring Area while considering uncertain flight durations for each flight. The tabu search algorithm was selected to solve the problem. The stochastic solution and deterministic solution results were compared to show the benefits of the stochastic solution. The average sample approximation technique was applied to this problem, and enhancement rates of the average fuel consumption per aircraft were 8.78% and 9.11% comparing the deterministic approach

关键词： Aircraft sequencing and scheduling problem stochastic programming Mixed-integer linear programming Fuel consumption Tabu search algorithm

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A two-stage stochastic programming model for seaport berth and channel planning with uncertainties in ship arrival and handling times

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2022年 167卷

作者： Liu, Baoli Li, Zhi-Chun Wang, Yadong Huazhong Univ Sci & Technol Sch Management Wuhan 430074 Peoples R China Dalian Maritime Univ Coll Transportat Engn Dalian 116026 Peoples R China Nanjing Univ Sci & Technol Sch Econ & Management Nanjing 210094 Peoples R China

The limited availability of berths and channels is generally the bottleneck restricting the capacity of a seaport and thus resulting in traffic congestion. Optimizing the operations of the berths and channels has been recognized as a more economic avenue for mitigating seaport traffic congestion compared with channel dredging and berth expanding that needs significant capital and time costs. This paper presents a two-stage stochastic mixed integer linear programming model for the seaport berth and channel planning, aiming to minimize the expected total weighted completion times of ships under uncertain ship arrival times and ship handling durations. The first stage decides the berth allocation of ships under uncertainty. In the second stage, the channel planning, including the selection of lanes, assignment of tugboats, and sequencing of ships, is determined after the uncertainty has been realized. To effectively solve the model, we propose two tailored decomposition methods, that is, the stage decomposition method and the decomposition-based heuristic algorithm (DHA). Then, a lower bound of the problem is derived to evaluate the quality of the solution. Numerical experiments on Tianjin Port of China show the satisfactory performance of these two proposed methods. Especially, the DHA is able to obtain near-optimal solutions with the average optimality gap less than 3% within four-hour computational time for the instances up to 500 scenarios and 190 ship movements. Some managerial insights are obtained to guide the operations of the port.

关键词： Port operations Berth allocation Ship scheduling Tugboat assignment stochastic programming

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Reducing transaction costs for interest rate risk hedging with stochastic programming

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2022年第3期302卷 1282-1293页

作者： Blomvall, Jorgen Hagenbjork, Johan Linkoping Univ Dept Management & Ind Engn SE-58183 Linkoping Sweden

Traditional methods for hedging interest rate risk do not take transaction costs into account as they aim to eliminate all risk. We propose a two-stage stochastic programming model for hedging interest rate risk where transaction costs are weighed against portfolio variance. High-quality measurements of term structures enable us to extract the systematic risk factors and make precise estimates of the perceived transaction costs. The hedging cost is weighed against the reduction in portfolio variance by using an adjustable hedging parameter. The hedging procedure is simulated on a daily basis in a realistic setting over an out-of-sample period from 2002 to 2018, and the results are compared to traditional hedging methods through detailed performance attribution. Using second-order stochastic dominance, we show that the proposed method is preferred by all risk-averse investors. (C) 2022 The Author(s). Published by Elsevier B.V.

关键词： Finance OR in banking Risk management stochastic programming

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A stochastic programming approach for heterogeneous variable message sign location problem for freeway networks

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TRANSPORTMETRICA A-TRANSPORT SCIENCE 2022年第1期18卷 99-124页

作者： Zhang, Guowei Zhu, Ning Zhong, Shiquan Ma, Shoufeng Han, Shanshan Tianjin Univ Coll Management & Econ Inst Syst Engn Tianjin 300072 Peoples R China FAW VOLKSWAGEN AUTOMOT CO LTD Changchun Peoples R China

Variable message signs (VMS) are electronic signage systems that display real-time traffic information to drivers to mitigate congestion and reduce travel time. We propose a heterogeneous VMS location problem based on a stochastic model of accidents on a freeway network. We consider both gantry and cantilever mounted VMS that displays both passive and active real-time messages. The problem is formulated as a two-stage stochastic programming model. The first-stage model determines the location and type of VMS installation. The second stage evaluates the performance of VMS location solutions by minimizing travelers' travel time and the penalty for misleading guidance. The model is formulated as a mixed-integer linear programming (MILP) problem that can be solved using the Benders decomposition (BD) algorithm. The Nguyen-Dupuis and Sioux-Fall networks are used to verify the effectiveness of the proposed models. We believe this study will provide practical guidance to freeway administrators.

关键词： Variable message sign stochastic programming location problem traffic accident Benders decomposition

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