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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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Day-ahead multi-criteria energy management of a smart home under different electrical rationing scenarios

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RENEWABLE ENERGY FOCUS 2024年 51卷

作者： Issa, Haala Haj Abedini, Moein Hamzeh, Mohsen Anvari-Moghaddam, Amjad Univ Tehran Coll Engn Sch Elect & Comp Engn Tehran Iran Aalborg Univ Dept Energy AAU Energy DK-9220 Aalborg Denmark Damascus Univ Sch Elect & Mech Engn Damascus Syria

With the recent global energy crisis, some countries have implemented electrical rationing (ER), making it necessary for smart homes to play a pivotal role in optimizing energy consumption and contributing to sustainable practices. To effectively manage smart home consumption, a stochastic programming approach for a grid-connected smart home energy management system (SHEMS) is proposed in this paper. The system includes PV, battery, diesel, and gas-based heating/cooling systems (HCS). Additionally, a demand response program (DRP) has been employed under time-of-use tariffs in the Syrian energy market. The main objective is to minimize the day-ahead expected cost and consumer discomfort by optimizing the operation of dispatchable units and loads. To manage the risks associated with the expected cost due to potential uncertainties in PV energy generation and electrical rationing programs, the conditional value-at-risk (CVaR) approach is adopted. Two methods are proposed to model the uncertainty in PV energy generation;interval bands and interval-based scenarios. The problem is modeled as a mixed-integer non-linear programming (MINLP) model, and coded in GAMS to test different cases. Based on the results obtained, substantial reductions reached 56.2% in worst-case cost scenarios when employing concurrent DRP-risk management.

关键词： Electrical rationing Smart home Energy management stochastic programming Demand response Energy market Conditional value at risk

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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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Optimization and self-dispatching of hydro-power companies in the electricity market 2

Optimization and self-dispatching of hydro-power companies i...

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2022 2nd International Conference on Power System and Energy Internet, PoSEI 2022

作者： Liang, Zhencheng Liang, Qingqing Li, Ling Luo, Cuiyun Dispatching Control Center of Guangxi Power Grid Corporation Guangxi Nanning China Xingjian College of Arts and Sciences Guangxi University Nanning China

The deepening reform of the power system has resulted in increased competition between electricity market participants. The ADP method is applied to solve the optimal self-dispatch problem of hydro-power companies under uncertain conditions. Firstly, according to the characteristics of hydropower generation technology and self-dispatching, the operation model of hydropower is given. Then, according to the organization and trading behavior of the forward contract market and day-ahead market, a medium and long-term contract quantity decision framework based on stochastic programming is given. Based on the stochastic programming decision framework, the ADP method is used to solve the generation and water decisions in each stage, and the distribution strategy of the electricity quantity of forward transactions and day-trading electricity quantity is obtained. Finally, an example is given to demonstrate the effectiveness of the proposed model and ADP method. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： stochastic programming

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Multi-period emergency facility location-routing problems under uncertainty and risk aversion

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SOCIO-ECONOMIC PLANNING SCIENCES 2024年 96卷

作者： Hu, Qing-Mi Hu, Yan Li, Xiaoping Jiangsu Univ Sci & Technol Sch Econ & Management Zhenjiang 212100 Peoples R China

This paper addresses a multi-period emergency facility location-routing problem, in which the uncertainties in material demands and transportation time, as well as dynamic inventory replenishment and carryover are incorporated in the design of multi-level emergency logistics networks. To measure the risks stemming from uncertain transportation time, mean-CVaR method is used. Then, a risk-averse stochastic programming model for the presented problem is formulated to minimize the total rescue time of the network. Moreover, a genetic algorithm is developed to solve the proposed model. Extensive numerical experiments including the randomly generated instances and a case study on the Wenchuan earthquake in China are conducted to verify the effectiveness of the presented model and algorithm. Experimental results show that the genetic algorithm significantly performs better than the Gurobi solver in terms of both solution quality and solution time.

关键词： Emergency facility location-routing Uncertainty Dynamic inventory replenishment and carryover Risk-averse stochastic programming Genetic algorithm

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Integrated emergency medical supply planning considering multiple supply channels in healthcare coalitions

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INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION 2024年 113卷

作者： Xu, Aocheng Wang, Qingyi Sichuan Univ Business Sch Chengdu 610064 Peoples R China Natl Univ Singapore Dept Ind Syst Engn & Management Singapore 117576 Singapore

Emergency medical supplies are crucial for the successful disaster response of healthcare coalitions. In practice, a healthcare coalition can obtain emergency medical supplies from three channels, i.e., supply pre-positioning, contracted reserve and emergency procurement, which, however, are not planned integrally in the literature. To fill the research gap, this study proposes a two-stage stochastic programming model for integrated emergency medical supply planning considering multiple supply channels in healthcare coalitions. In the first stage before disasters, decisions on emergency medical supply pre-positioning and signing of two types of medical supply procurement contracts are determined. In the second stage after disasters, decisions of emergency supply procurement, contract implementation, and supply transshipment are optimized based on the first-stage decisions and the realized uncertain disaster impacts. To show the effectiveness of our model and obtain managerial insight, we develop four comparison models and conduct a case study on the healthcare coalition of West China Hospital in China. This study highlights the great benefits of supplementing the pre-positioning of emergency medical supplies with multi-type contracted reserve in healthcare coalitions and emphasizes the importance of strengthening cooperation with suppliers and encouraging all member hospitals to implement the contracted reserve.

关键词： Emergency medical supply planning Supply pre-positioning Contracted reserve Healthcare coalition stochastic programming

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Spatial-Temporal Power Balance Method for Active Distribution Systems Based on Time Series Operation Simulation with Source-Load-Storage Coordination 6

Spatial-Temporal Power Balance Method for Active Distributio...

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6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022

作者： Wang, Zhe Zhu, Shitian Luo, Tao Wu, Xuan Feng, Shaoting Luo, Fengzhang State Grid Tianjin Electric Power Company Tianjin300010 China Tianjin University Key Laboratory of Smart Grid of Ministry of Education Tianjin300072 China

ISBN: (纸本)9798350347159

With the construction and development of new-type power system with a gradually increasing proportion of new energies, large-scale distributed generations are widely integrated, electric energy substitution is gradually accelerated, load interaction is continuously enhanced, a fundamental change is taking place. In the traditional power distribution system, the clear role boundaries of power supply and power consumption are gradually blurred, the uncertainty of source and load increases, and the difficulty of balancing supply and demand increases. Therefore, this paper focuses on new-type power distribution system's hierarchical partition spatial-temporal balance problem. Firstly, various flexible resource model that participate in the new-type power distribution system's supply and demand balance are constructed. Then, a new-type power distribution system's hierarchical partition spatial-temporal balance model based on operation simulation and stochastic programming is constructed. Finally, after the analysis and comparison of case studies, the proposed model and method are verified. The results show that the proposed method can realize the optimization of the regional supply and demand balance, and improve the security and economics of the distribution system. © 2022 IEEE.

关键词： stochastic programming

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Comparison of Linear Power Flow Approximations in the Context of Winter Storm Planning

Comparison of Linear Power Flow Approximations in the Contex...

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IISE Annual Conference and Expo 2022

作者： Austgen, Brent Kutanoglu, Erhan Hasenbein, John J. Operations Research and Industrial Engineering Program The University of Texas at Austin AustinTX United States

ISBN: (纸本)9781713858072

The resilience of the Texas power grid has been tested by winter storms and the attendant cold on multiple occasions. Notable events include the United States cold wave of December 1989, the Groundhog Day Blizzard of 2011, and most recently Winter Storm Uri of 2021. With these events in mind, we propose a two-stage stochastic programming model for informing winterization investment decisions for generators. First-stage decisions pertain to investments, and second-stage decisions are power generation and load shed in an optimal power flow problem. The objective is to minimize the expected load shed across a set of plausible winter storm outage scenarios, each featuring multiple simultaneous generator outages and derates. We apply the model to a synthetic power grid instance and use scenarios developed from Winter Storm Uri generator outage and derate data. We assess and compare the optimal first-stage decisions that result from using different approximations of AC power flow to comprise the second-stage problem. © 2022 IISE Annual Conference and Expo 2022. All rights reserved.

关键词： stochastic programming

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Green retailer: A stochastic bi-level approach to support investment decisions in sustainable energy systems

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OPERATIONS RESEARCH PERSPECTIVES 2024年 12卷

作者： Beraldi, Patrizia Lab Financial Engn & Risk Management Dept Mech Energy & Management Engn Via P Bucci I-87036 Arcavacata Di Rende Cosenza Italy

This paper presents a bi-level approach to support retailers in making investment decisions in renewable -based systems to provide clean electricity. The proposed model captures the strategic nature of the problem and combines capacity sizing decisions for installed technologies with pricing decisions regarding the electricity tariffs to offer to a reference end -user, representative of a class of residential prosumers. The interaction between retailer and end -user is modeled using the Stackelberg game framework, with the former acting as a leader and the latter as follower. The reaction of the follower to the electricity tariff affects the retailer's profit, which is calculated as the difference between the revenue generated from selling electricity and the total investment, operation and management costs. To account for uncertainty in wholesale electricity prices, renewable resource availability and electricity request, the upper -level problem is formulated as a two -stage stochastic programming model. First -stage decisions refer to the sizing of installed technologies and electricity tariffs, whereas second -stage decisions refer to the operation and management of the designed system. The model also incorporates a safety measure to control the average profit that can be achieved in a given percentage of worst -case situations, thus providing a contingency against unforeseen changes. At the lower level, the follower reacts to the offered tariffs by defining the procurement plan in terms of energy to purchase from the retailer or potential competitors, with the final aim of minimizing the expected value of the electricity bill. A tailored approach that exploits the specific problem structure is designed to solve the proposed formulation and extensively tested on a realistic case study. The numerical results demonstrate the efficiency of the proposed approach and validate the significance of explicitly dealing with the uncertainty and the importance of incorporat

关键词： Green electricity retailer Sustainable energy system Bi-level optimization stochastic programming

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Multistage Inventory Model with Probabilistic and Quantile Criteria 21st

Multistage Inventory Model with Probabilistic and Quantile...

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21st International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2022

作者： Ivanov, Sergey V. Mamchur, Aleksandra V. Volokolamskoe Shosse 4 Moscow125993 Russia

ISBN: (纸本)9783031096068

We consider a multistage inventory model. At each stage, a company determines order quantities of several products to satisfy a demand. The demand is described by a discrete random process. If the demand on a product is more than inventory level of this product, the company has to make additional ordering by market price. Otherwise, the company has to hold the rest of this product by a known price. The company can use a storage. The capacity of the storage is bounded. We consider two objective functions in this model. The first objective function is the probability that the losses are less or equal to a desirable level. The second one is the quantile of losses. To solve the considered problem we reduce them to mixed integer linear programming problems. This reduction is based on introducing auxiliary variables. We suggest conditions ensuring the equivalence of the original problems and the reduced ones. Also, we consider the problems when the distribution of the random process is unknown. For this case, we prove the convergence of the sample approximation method. Numerical results are discussed. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： stochastic programming

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