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Optimal postponement in supply chain network design under uncertainty: an application for additive manufacturing

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2021年第17期59卷 5198-5215页

作者： Ramon-Lumbierres, Daniel Heredia Cervera, F. Javier Minguella-Canela, Joaquim Muguruza-Blanco, Asier Univ Politecn Catalunya BarcelonaTech Dept Stat & Operat Res GNOM C5 BldgNorth CampusJordi Girona 1-3 Barcelona 08034 Spain Univ Politecn Catalunya BarcelonaTech Fundacio Ctr CIM Barcelona Spain

This study presents a new two-stage stochastic programming decision model for assessing how to introduce some new manufacturing technology into any generic supply and distribution chain. It additionally determines the optimal degree of postponement, as represented by the so-called customer order decoupling point (CODP), while assuming uncertainty in demand for multiple products. To this end, we propose here the formulation of a generic supply chain through an oriented graph that represents all the deployable alternative technologies, which are defined through a set of operations that are characterised by lead times and cost parameters. Based on this graph, we develop a mixed integer two-stage stochastic programme that finds the optimal manufacturing technology for meeting each market's demand, each operation's optimal production quantity, and each selected technology's optimal CODP. We also present and analyse a case study for introducing additive manufacturing technologies.

关键词： Manufacturing postponement stochastic programming supply chain strategy 3D printing additive manufacturing

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A reinforcement learning approach for selecting infill drilling locations considering long-term production planning in mining complexes with supply uncertainty

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MINING TECHNOLOGY-TRANSACTIONS OF THE INSTITUTIONS OF MINING AND METALLURGY 2024年第2期133卷 176-187页

作者： Levinson, Zachary Dimitrakopoulos, Roussos McGill Univ Dept Min & Mat Engn COSMO Stochast Mine Planning Lab FDA Bldg3450 Univ St Montreal PQ H3A 0E8 Canada

Simultaneous stochastic optimisation frameworks provide a method for optimising long-term production schedules in mining complexes that aim to maximise net present value and manage risk related to supply uncertainty. The uncertainty and local variability related to the quality and quantity of material in the mineral deposits are modelled with a set of stochastic orebody simulations, an input into the simultaneous stochastic optimisation framework. Infill drilling provides opportunities to collect additional information associated with the mineral deposits, which can inform future production scheduling decisions. A framework is developed for optimising infill drilling locations with a criterion that seeks areas that directly affect long-term planning decisions and requires the use of geostatistical simulations. Actor-critic reinforcement learning is applied to identify infill drilling locations in a copper mining complex using this criterion. The case study demonstrates that adapting production scheduling decisions given additional information has the potential to improve the associated production and financial forecasts and identifies a stable area for infill drilling.

关键词： infill drilling simultaneous stochastic optimisation reinforcement learning stochastic programming long-term planning value of information

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A Two-Stage stochastic Distribution Network Restoration Model with Waste Incineration Power Plants as Black-Start Power Resources 7

A Two-Stage Stochastic Distribution Network Restoration Mode...

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7th Asia Conference on Power and Electrical Engineering, ACPEE 2022

作者： Shi, Shanshan Zhou, Jian Su, Yun Wei, Xinchi Zhou, Sunyang Liu, Haoming State Grid Corporation of China Shanghai Electric Power Research Institute Shanghai China Hohai University College of Energy and Electrical Engineering Nanjing China

ISBN: (纸本)9781665418195

Waste Incineration Power Plant (WIPP) is a promising sustainable and environmentally-friendly generation technique. This paper explores the impacts of WIPPs as black-start resources on distribution network restoration. Specifically, the black-start and operation characteristics of WIPPs equipped with gas storage tanks are analyzed and modeled. Then, a two-stage stochastic distribution network restoration model is established with WIPPs as black-start resources and uncertainties from distributed renewable generations. The first stage is to solve the recovery sequence of nodes and lines, and the second stage comprises the scenario-wise operation of distributed generators and dispatchable loads. The objective is to maximize the expected restored load demand while comprehensively satisfying restoration constraints, including the black-start and operation constraints of WIPPs. The proposed restoration model is transformed into a mixed-integer linear programming (MILP) based on the linearization of AC power flow. An example analysis on an improved IEEE 13-bus distribution system demonstrated the impacts of WIPP on distribution network restoration. © 2022 IEEE.

关键词： stochastic programming

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Power/Hydrogen Optimal stochastic Scheduling Considering Frequency Regulation Markets 5

Power/Hydrogen Optimal Stochastic Scheduling Considering Fre...

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5th IEEE International Conference on Smart Systems and Technologies, SST 2022

作者： Khazali, Amirhossein Torkzadeh, Roozbeh Chamorro, Harold R. Makolo, Peter Sood, Vijay K. Zamora, Ramon Grid Planning Deputy Iran Grid Management Company Tehran Iran Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands Department of Electrical Engineering KTH Royal Institute of Technology Stockholm Sweden Department of Electrical Engineering Auckland University of Technology Auckland New Zealand Department of Electrical Engineering Ontario Tech University Oshawa Canada

ISBN: (数字)9781665482158

ISBN: (纸本)9781665482158

This paper presents a novel optimal offering framework to incorporate hydrogen system potential for frequency regulation goals. Furthermore, the presented model considers the possibility of submitting bids for a day-ahead hydrogen market. To harness the uncertainty of AGC (automatic generation control) signals, the problem is formulated as a two-level stochastic programming approach where in the first stage, the day-ahead market is cleared, and in the second stage, which is related to the real-time market, the up and down capacities of the hydrogen system are determined for each hour. The results indicate that the presented model is able to maximize the income of the integrated power/hydrogen system by determining the optimal scheduling of each of these devices and increase the income of the system by taking advantage of the frequency regulation market and dedicating a capacity of the electrolyzer and fuel cell to this market. © 2022 IEEE.

关键词： stochastic programming

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Overview of Power System Planning under Uncertainty 2

Overview of Power System Planning under Uncertainty

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2nd International Conference on Electrical Engineering and Control Science, IC2ECS 2022

作者： Zhao, Yuanshang Lin, Weifang China Electric Power Research Institute Beijing100192 China

ISBN: (纸本)9798350399165

With the gradual increase of the proportion of renewable energy generation dominated by wind power and photovoltaic power and the change of load characteristics, the source-load uncertainty of power system will be one of the new power system characteristics with high proportion of new energy. Therefore, at this stage, the uncertainty method should be mainly used for power system planning. For the planning of power system under uncertain conditions, the uncertain variables that affect the planning of power system are first introduced, including new energy output and load forecasting, new factors of power system, investment cost, policy and environment. Then, the application of stochastic programming method in power system uncertainty planning is introduced, including the general scenario model of stochastic programming and the stochastic programming model of power system with opportunity constraints, and the probability prediction of uncertain variables in stochastic programming is introduced. Secondly, the application of power system robust optimization method in power system uncertain planning is introduced, including classical robust optimization method and distributed robust optimization method, and the interval prediction of uncertain variables in classical robust optimization method is introduced. stochastic programming and classical robust optimization should study how to better describe the information of uncertain variables in the future. At present, the distributed robust optimization method should first solve the planning adaptability problem of high-proportion new energy power system. Finally, the future research on uncertain planning of power system is prospected. © 2022 IEEE.

关键词： stochastic programming

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Optimal investment for a retirement plan with deferred annuities

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INSURANCE MATHEMATICS & ECONOMICS 2021年 98卷 51-62页

作者： Owadally, Iqbal Jang, Chul Clare, Andrew City Univ London Business Sch 106 Bunhill Row London EC1Y 8TZ England

We construct an optimal investment portfolio model with deferred annuities for an individual investor saving in a retirement plan. The objective function consists of power utility in terms of consumption of all secured retirement income from the deferred annuity purchases, as well as bequest from remaining wealth invested in equity, bond, and cash funds. The asset universe is governed by a vector autoregressive model incorporating the Nelson-Siegel term structure and equity returns. We use multi-stage stochastic programming to solve the optimization problem numerically. Deferred annuity purchases are made continuously over the working lifetime of the investor, increasing particularly in the years before retirement. The investment strategy hedges price changes in deferred annuities, and bond holding and deferred annuity purchases increase when interest rates are high. Optimal investment and deferred annuity choices depend on realized and expected values of state variables. The optimal strategy is also compared with typical retirement plan strategies such as glide paths. Our results provide support for deferred annuities as a major source of retirement income. (C) 2021 Elsevier B.V. All rights reserved.

关键词： stochastic programming Retirement planning Deferred annuities Nelson-Siegel model Vector autoregressive Glide path

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A resilient inventory management of pharmaceutical supply chains under demand disruption

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COMPUTERS & INDUSTRIAL ENGINEERING 2023年 180卷

作者： Pathy, Soumya Ranjan Rahimian, Hamed Clemson Univ Dept Ind Engn Clemson SC 29634 USA

Inspired by the global supply chain disruptions caused by the COVID-19 pandemic, we study optimal procurement and inventory decisions for a pharmaceutical supply chain over a finite planning horizon. To model disruption, we assume that the demand for medical drugs is uncertain and shows spatiotemporal variability. To address demand uncertainty, we propose a two-stage optimization framework, where in the first stage, the total cost of pre-positioning drugs at distribution centers and its associated risk is minimized, while the second stage minimizes the cost of recourse decisions (e.g., reallocation, inventory management). To allow for different risk preferences, we propose to capture the risk of demand uncertainty through the expectation and worst-case measures, leading to two different models, namely (risk-neutral) stochastic programming and (risk-averse) robust optimization. We consider a finite number of scenarios to represent the demand uncertainty, and to solve the resulting models efficiently, we propose L-shaped decomposition-based algorithms. Through extensive numerical experiments, we illustrate the impact of various parameters, such as travel time, product's shelf life, and waste due to transportation and storage, on the supply chain resiliency and cost, under optimal risk-neutral and risk-averse policies. These insights can assist decision makers in making informed choices.

关键词： Resilient pharmaceutical supply chain Risk aversion stochastic programming Robust optimization Benders' decomposition

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Safe-Exploration of Control Policies from Safe-Experience via Gaussian Processes 16th

Safe-Exploration of Control Policies from Safe-Experience vi...

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16th International Conference on Learning and Intelligent Optimization, LION 16 2022

作者： Candelieri, Antonio Ponti, Andrea Archetti, Francesco University of Milano-Bicocca Milan Italy

ISBN: (纸本)9783031248658

. Control of many real-life systems strongly relies on the knowledge of a domain expert, who usually adopts a safe control policy to deal with uncertainty. The term safe means that the policy is aimed at avoiding system’s disruptions or relevant deviations from the desired behaviour, usually at the cost of sub-optimal performances. This paper proposes a statistically-sound approach which exploits the collected experience to safe-explore new policies by assuming a reasonable risk in terms of safety while improving performances. Gaussian Process regression is the core of the approach, providing a probabilistic approximation of both system’s dynamics and performances, depending on historical data related to the application of the safe policy. Being a probabilistic model, Gaussian Process provides both an estimate of the level of safety and, more important, the associated predictive uncertainty, which is crucial for implementing the safe-exploration of new efficient policies. The approach allows to avoid the typically expensive implementation of a digital twin of the system, required in the case of simulation-optimization approaches, as well as the formulation as a stochastic programming problem. Results on two case studies, inspired by real-life systems, are presented, showing an improvement in terms of performances with respect the initial safe policy, with reasonable safety of the systems.

关键词： stochastic programming

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Intraday PV-storage power reporting model considering temporal correlation of forecast error 5

Intraday PV-storage power reporting model considering tempor...

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Liu, Shujun Wang, Bo Zhuang, Weihuan Zhao, Weiran Co. Ltd. Beijing China China Three Gorges Corporation Fujian Energy Investment Co. Ltd. Engineering Management Department Fuzhou China China Electric Power Planning & Engineering Institute Technology Innovation and Industrial Planning Center Beijing China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

This paper proposes a strategy for reporting the intraday output plan of photovoltaic (PV) power plants considering the power correction of energy storage devices. First, an intraday PV power scenario generation method which considers the temporal correlation of intraday rolling forecasts is proposed. Secondly, considering the adjustment capability of energy storage devices, an intraday joint power reporting model of PV-storage system at different time periods is established. Finally, based on the actual data of the PV-storage power station in China, the simulation is carried out to verify the effectiveness of the proposed method. © 2022 IEEE.

关键词： stochastic programming

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Capacity investment and inventory planning for a hybrid manufacturing - remanufacturing system in the circular economy

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2021年第8期59卷 2450-2478页

作者： Reddy, K. Nageswara Kumar, Akhilesh Indian Inst Technol Dept Ind & Syst Engn Kharagpur W Bengal India

Remanufacturing through circular economy conserves energy and materials while creating economic growth and employment. Thus, it is imperative to develop better systems that optimise the use of resources, maximise the value of the product, and minimise the total cost. Towards this, we present a two-stage stochastic linear model for a make-to-order hybrid manufacturing-remanufacturing production system by integrating capacity and inventory decisions. We consider the uncertainty in demand, core returns rate and yield to impose flexibility as both operations are considered with a collective production capacity on the same assembly line. We have considered a setting where demand for new and remanufactured products does not cannibalise each other's demand (e.g. new parts for original equipment and remanufactured parts for independent aftermarket). Further, the capacity utilisation by core returns is considered in two ways: less capacity intensive case and more capacity intensive case. The developed model is solved for optimal inventory and capacity levels along with production quantities by maximising utilisation of resources and profit. We also present a closed-form solution by demand space partition to deduce the optimal policy of the firm. Based on our analysis, we have presented settings where remanufacturing can perfectly substitute manufacturing.

关键词： circular economy remanufacturing capacity planning inventory decisions stochastic programming

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