检索结果-内蒙古大学图书馆

Fast scenario reduction by conditional scenarios in two-stage stochastic MILP problems

OPTIMIZATION METHODS & SOFTWARE 2022年第1期37卷 23-44页

作者： Beltran-Royo, C. King Juan Carlos Univ Comp Sci Stat & Operat Res Dept Madrid Spain

A common approach to model stochastic programming problems is based on scenarios. An option to manage the difficulty of these problems corresponds to reduce the original set of scenarios. In this paper we study a new fast scenario reduction method based on Conditional Scenarios (CS). We analyse the degree of similarity between the original large set of scenarios and the small set of conditional scenarios in terms of the first two moments. In our numerical experiment, based on the stochastic capacitated facility location problem, we compare two fast scenario reduction methods: the CS method and the Monte Carlo (MC) method. The empirical conclusion is twofold: On the one hand, the achieved expected costs obtained by the two approaches are similar, although the MC method obtains a better approximation to the original set of of scenarios in terms of the moment matching criterion. On the other hand, the CS approach outperforms the MC approach with the same number of scenarios in terms of solution time.

关键词： stochastic programming scenario reduction Monte Carlo sampling conditional scenario stochastic capacitated facility location problem

来源：评论

学校读者我要写书评

暂无评论

An Online Approach to Balancing the Energy Consumption for IoT Sensors in UAV-based MEC Systems 16

An Online Approach to Balancing the Energy Consumption for I...

引用

16th International Conference on Wireless Communications and Signal Processing, WCSP 2024

作者： Li, Yang Lin, Xiaohui Bi, Suzhi Dai, Mingjun Su, Gongchao College of Electronics and Information Engineering Shenzhen University Shenzhen China School of Computer Science Kashi University Kashi China

ISBN: (纸本)9798350390643

In this paper, we consider an unmanned aerial vehicle-enabled (UAV-enabled) Mobile Edge Computing (MEC) Internet of Things (IoT) system consisting of multiple energy harvesting devices. In the system, the UAV acts as the edge computing platform providing computation service to the devices. We assume that the energy and sensing data arrive at the devices stochastically. As the amount of energy harvested by devices can differ significantly, we attempt to balance the energy consumption among devices thus avoiding the loss of devices due to the depletion of the battery energy. To ensure energy fairness, we employ an a-utility function, which incorporates the device's remaining energy and energy expenditure. Without any future knowledge of the data and energy arrivals, our objective is to design an online algorithm to jointly optimize the long-term system throughput and utility, while satisfying the stability requirement of the data queue. We formulate the problem as multi-stage stochastic programming that involves functions of time averages and propose an online algorithm based on the perturbed Lyapunov optimization technique. Due to the time-coupling of different variables, we first transform the original problem into a multi-stage stochastic optimization problem involving only time averages. Then, we utilize the Lyapunov optimization method to decouple the transformed problem into a series of per-slot deterministic subproblems. In each slot, we alternatively optimize the auxiliary variables, the data sensing rate, the computation offloading, the communication resource allocation, and the trajectory of the UAV. Simulation results show that the online algorithm can maintain the stability of the data queue. Additionally, we observe a tradeoff between the system's lifetime and throughput when adjusting the parameter α, as well as a tradeoff between throughput and delay for the Lyapunov method. © 2024 IEEE.

关键词： stochastic programming

来源：评论

学校读者我要写书评

暂无评论

Optimization Methodologies for Uncertainty Characterization with Large-Scale Renewables Integration 4th

Optimization Methodologies for Uncertainty Characterization ...

引用

4th International Conference on Energy Power and Automation Engineering, ICEPAE 2023

作者： Wang, Miao Li, Zeke Sun, Bo Fan, Haiwei Hu, Xin Ding, Linglong China Electric Power Research Institute Beijing100192 China State Grid Fujian Electric Power Co. LTD Fuzhou350003 China State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789819988778

The increasing penetration of renewable sources into the power grid brings uncertainty of active power on both the generation side and demand side also increases significantly. Power grid dispatching needs to be transformed from deterministic optimization to uncertain optimization. The scenario-based, stochastic programming, and robust optimization methods are optimization methods that can be used to characterize the uncertainty of renewable energy generation and improve power grid dispatching. This paper utilizes three methods to characterize the uncertainty of renewable output and employs a series of techniques to convert these methods into optimization that can be directly handled by existing solvers. An evaluation of each method is provided at the end. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： stochastic programming

来源：评论

学校读者我要写书评

暂无评论

A two-stage stochastic optimization model for the retail multiskilled personnel scheduling problem: a k-chaining policy with k ≥ 2

引用

MATHEMATICAL BIOSCIENCES AND ENGINEERING 2022年第1期19卷 892-917页

作者： Andrea Mercado, Yessica Augusto Henao, Cesar Gonzalez, Virginia, I Univ Norte Dept Ind Engn Km 5 Via Puerto Colombia Barranquilla Colombia

Considering an uncertain demand, this study evaluates the potential benefits of using a multiskilled workforce through a k-chaining policy with k >= 2. For the service sector and, particularly for the retail industry, we initially propose a deterministic mixed-integer linear programming model that determines how many employees should be multiskilled, in which and how many departments they should be trained, and how their weekly working hours will be assigned. Then, the deterministic model is reformulated using a two-stage stochastic optimization (TSSO) model to explicitly incorporate the uncertain personnel demand. The methodology is tested for a case study using real and simulated data derived from a Chilean retail store. We also compare the TSSO approach solutions with the myopic approaches' solutions (i.e., zero and total multiskilling). The case study is oriented to answer two key questions: how much multiskilling to add and how to add it. Results show that TSSO approach solutions always report maximum reliability for all levels of demand variability considered. It was also observed that, for high levels of demand variability, a k-chaining policy with k >= 2 is more cost-effective than a 2-chaining policy. Finally, to evaluate the conservatism level in the solutions reported by the TSSO approach, two truncation types in the probability density function (pdf) associated with the personnel demand were considered. Results show that, if the pdf is only truncated at zero (more conservative truncation) the levels of required multiskilling are higher than when the pdf is truncated at 5th and 95th percentiles (less conservative truncation).

关键词： multiskilling cross-training chaining personnel scheduling stochastic programming retail

来源：评论

学校读者我要写书评

暂无评论

Flexibility and real options analysis in power system generation expansion planning under uncertainty

引用

IISE TRANSACTIONS 2022年第9期54卷 832-844页

作者： Caunhye, Aakil M. Cardin, Michel-Alexandre Rahmat, Muhammad Univ Edinburgh Business Sch Edinburgh Midlothian Scotland Imperial Coll London Dyson Sch Design Engn London England Minist Finance Singapore Singapore

Over many years, there has been a drive in the electricity industry towards better integration of environmentally friendly and renewable generation resources for power systems. Such resources show highly variable availability, impacting the design and performance of power systems. In this article, we propose using a stochastic programming approach to optimize Generation Expansion Planning (GEP), with explicit consideration of generator output capacity uncertainty. Flexibility implementation - via real options exercised in response to uncertainty realizations - is considered as an important design approach to the GEP problem. It more effectively captures upside opportunities, while reducing exposure to downside risks. A decision-rule-based approach to real options modeling is used, combining conditional-go and finite adaptability principles. The solutions provide decision makers with easy-to-use guidelines with threshold values from which to exercise the options in operations. To demonstrate application of the proposed methodologies and decision rules, a case study situated in the Midwest United States is used. The case study demonstrates how to quantify the value of flexibility, and showcases the usefulness of the proposed approach.

关键词： Flexibility real options stochastic programming power systems risk analysis systems design and analysis uncertainty

来源：评论

学校读者我要写书评

暂无评论

Transparent structured products for retail investors

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2022年第2期302卷 752-767页

作者： Kallio, Markku Halme, Merja Hardoroudi, Nasim Dehghan Aspara, Jaakko Aalto Univ Dept Informat & Serv Econ Sch Business POB 21210 FI-00076 Aalto Finland Hanken Sch Econ PB 479 FI-00101 Helsinki Finland

Structured investment products (SPs) are derivative securities whose return is contingent on the return of their underlying assets, such as a certain stock market index. SPs have been criticized for being complex and costly on the inside, while attracting retail investors with emotionally appealing promises, on the surface, to provide tempting yields and protection for the capital invested. To circumvent such criticism, we consider transparent SPs (TSPs), which simply offer a lower and upper limit on annual return (after costs and fees) as well a transparent rule defining the return based on the return of the underlying asset. We study TSPs using both empirical and theoretical approaches. An empirical survey of real investors with best-worst scaling as well as theoretical analyses based on utility theory and multi-stage stochastic programming (MSSP) show that moderately priced TSPs are competitive in comparison with other investment products, such as index funds. Furthermore, retail investors actually exhibit substantial preference for TSPs with partial capital guarantees, over and above SPs with the superficially tempting, full capital guarantees. A theoretical, MSSP-based analysis similarly confirms that including TSPs in an investment portfolio can yield substantial gains in certainty equivalent annual return. The results further indicate that perceived gains from TSPs are sensitive to costs, market imperfections, and interest rates, as well as private preferences and stock market expectations of retail investors. This demonstrates how MSSP can be applied to financial engineering for successful implementation of TSPs in future financial markets. (C) 2022 The Authors. Published by Elsevier B.V.

关键词： Finance Structured products stochastic programming Utility theory Discrete choice

来源：评论

学校读者我要写书评

暂无评论

Research on cross-building energy storage management system based on reinforcement learning 7

Research on cross-building energy storage management system ...

引用

2024 7th International Conference on Power Electronics and Control Engineering, ICPECE 2024

作者： Xin, Ming Wang, Yanli Zhang, Ruizhi Zhang, Jibin Liu, Xinan State Grid Heilongjiang Electric Power Company Limited Heilongjiang Harbin150090 China School of Management Harbin Institute of Technology Heilongjiang Harbin150001 China

This study considers a cross-building energy storage system in which the objective function of each step is a piecewise linear function of decision variables and state variables. Therefore, the objective function can be modeled as piecewise linear programming and then transformed into a mixed integer linear programming (MILP) problem. However, as a multi-stage stochastic programming problem in which we utilize approximate dynamic programming (ADP) to tackle the computational issues, we need to solve the objective function multiple times. To further decrease computational cost, we propose several approximate algorithms to determine variable splitting, which degrades the problem to a linear programming problem. We use approximate techniques to solve the problem and design experiments to verify our conclusion. Numerical experiments show that our algorithm greatly reduces the time needed to solve the problem under the condition of minimal loss of accuracy. The simulation experiment in a Python environment further proves that the cross-building energy storage management system based on energy routers and control centers is better than the energy system of each building working alone to maximize the benefits. © Published under licence by IOP Publishing Ltd.

关键词： stochastic programming

来源：评论

学校读者我要写书评

暂无评论

Keyword targeting optimization in sponsored search advertising: Combining selection and matching

引用

ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS 2022年 56卷

作者： Li, Huiran Yang, Yanwu Shanghai Customs Coll Sch Business Adm & Customs Affair Shanghai 201204 Peoples R China Huazhong Univ Sci & Technol Sch Management Wuhan 430074 Peoples R China

In sponsored search advertising (SSA), advertisers need to select keywords and determine matching types for selected keywords simultaneously, i.e., keyword targeting. An optimal keyword targeting strategy guarantees reaching the right population effectively. This paper aims to address the keyword targeting problem, which is a challenging task because of the incomplete information of historical advertising performance indices and the high uncertainty in SSA environments. First, we construct a data distribution estimation model and apply a Markov Chain Monte Carlo method to make inference about unobserved indices (i.e., impression and click -through rate) over three keyword matching types (i.e., broad, phrase and exact). Second, we formulate a sto-chastic keyword targeting model (BB-KSM) combining operations of keyword selection and keyword matching to maximize the expected profit under the chance constraint of the budget, and develop a branch-and-bound al-gorithm incorporating a stochastic simulation process for our keyword targeting model. Finally, based on a realworld dataset collected from field reports and logs of past SSA campaigns, computational experiments are conducted to evaluate the performance of our keyword targeting strategy. Experimental results show that, (a) BB-KSM outperforms seven baselines in terms of profit;(b) BB-KSM shows its superiority as the budget increases, especially in situations with more keywords and keyword combinations;(c) the proposed data distribution estimation approach can effectively address the problem of incomplete performance indices over the three matching types and in turn significantly promotes the performance of keyword targeting decisions. This research makes important contributions to the SSA literature and the results offer critical insights into keyword man-agement for SSA advertisers.

关键词： Keyword targeting Keyword matching Keyword selection Sponsored search advertising stochastic programming

来源：评论

学校读者我要写书评

暂无评论

The impact of multiple products and limited capacity on routine sourcing decisions

引用

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2022年第12期60卷 3728-3750页

作者： Freeman, Nickolas Narayanan, Arunachalam Univ Alabama Informat Syst Stat & Management Sci Tuscaloosa AL USA Univ North Texas Dept Informat Technol & Decis Sci Denton TX 76203 USA

We study the influence of limited capacity and multiple products on the optimal sourcing decisions for a manufacturer subject to supply and demand uncertainty. The manufacturer produces two products. The component of one product is sourced from two suppliers, one perfectly reliable and the other cheaper but unreliable, failing to deliver the order with some probability. We develop a mathematical model for a single-period setting and study the associated optimality conditions. Our results show that the supplier diversification strategy is significantly different when the buyer has limited capacity. Specifically, we find that single sourcing from an expensive and reliable supplier may be an optimal procurement strategy even when a cheaper option exists. In addition, when producing multiple products, the optimal sourcing strategy may hold inventory of one component to reduce the amount of capacity idling when the supply of a different component is disrupted. We use stochastic programming to validate our single-period findings in a multi-period setting. Although carrying inventory of finished products provides another tactic to mitigate supply uncertainty in a multi-period environment, we observe the key findings from single period, like single-sourcing from an expensive but reliable supplier, remain valid.

关键词： Supply chain risk management routine sourcing stochastic programming nonlinear programming

来源：评论

学校读者我要写书评

暂无评论

On the interaction between the design and operation under uncertainties of a simple distributed energy system

引用

COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING 2022年第6期41卷 2084-2095页

作者： Radet, Hugo Sareni, Bruno Roboam, Xavier UT3 CNRS LAPLACE INPT Toulouse France

Purpose The purpose of this study is toward a better understanding of the interplay between the design and the operation under uncertainties of a simple distributed energy system (DES), by analyzing the sensitivity of the operation strategy over the size of the assets. Design/methodology/approach A two-step framework is developed in this work: first, the equipment sizes are obtained solving an integrated design approach where an operation strategy F-d is embedded in a design loop;then, once the sizes have been fixed, the DES is evaluated with an operation strategy F-a (which can be the same as F-d). The operation strategies F-d and F-a are not necessarily the same, so the objective of the paper is to study the interplay between the design and the operation by varying the optimality level of the operation strategies in both phases. Findings The results show that the design of DES cannot be approached without considering its close relationship with the operation strategy. Indeed, the design method needs to be chosen according to the performance of the operation policy finally used in real life: no matter if the operation strategies are the same in both phases but they must lead to a similar level of optimality in terms of operating performance. Originality/value The originality of this work is to shed light on the importance of the operation strategy in the design procedure as it seems rarely addressed, to the best of the authors' knowledge, in the literature. Indeed, most of the paper dealing with stochastic design of DES solves single large two-stage problems without discussing the way power flows are finally controlled in real life. The optimal design and operation of DES is rarely addressed conjointly, this study aims at bridging the gap between these two isolated scientific communities.

关键词： Microgrids Distributed energy system Integrated optimal design Energy planning Energy management stochastic programming Uncertainties Optimal control Optimal design Design optimization methodology Robust design

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：