Article
Automation & Control Systems
Masako Kishida, Ahmet Cetinkaya
Summary: This paper considers stochastic linear quadratic control problems from the viewpoint of risks. The study focuses on three problems: finding the optimal feedback gain that minimizes the risk of the quadratic cost, solving the one-step problem, and addressing the infinite time horizon problem. The presented theorems are illustrated with numerical examples.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Margaret P. Chapman, Riccardo Bonalli, Kevin M. Smith, Insoon Yang, Marco Pavone, Claire J. Tomlin
Summary: This article develops a safety analysis method that is sensitive to the possibility and severity of rare harmful outcomes. The method assesses the maximum cost of stochastic systems using Conditional Value-at-Risk and provides computationally tractable underapproximations to risk-sensitive safe sets. The article also proposes a second definition for risk-sensitive safe sets and provides a tractable method for their estimation.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Engineering, Industrial
Andre Gustavo Carlon, Henrique Machado Kroetz, Andre Jacomel Torii, Rafael Holdorf Lopez, Leandro Fleck Fadel Miguel
Summary: This paper proposes a stochastic gradient based method for Risk Optimization problems, approximating failure probabilities using the Chernoff bound and solving the problem with a Stochastic Gradient Descent algorithm. The approach efficiently avoids direct computation of failure probabilities and their gradients.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Management
Zhenfeng Zou, Qinyu Wu, Zichao Xia, Taizhong Hu
Summary: This paper introduces and studies a class of convex risk measures called adjusted Renyi entropic Value-at-Risk (VaR), which quantifies risk by setting a threshold for Renyi entropic-VaR. It is linked to the (p + 1)-increasing convex order by choosing a benchmark for the risk threshold.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Automation & Control Systems
Masako Kishida, Masaaki Nagahara
Summary: This article deals with the risks associated with maximum hands-off control, aiming to minimize the length of non-zero control input. By considering stochastic systems and employing worst-case conditional value-at-risk, the study proposes two risk-aware maximum hands-off control problems and derives a risk-constrained sparse model predictive control method.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Mathematics, Applied
Dilan Ahmed, Fazlollah Soleymani, Malik Zaka Ullah, Hataw Hasan
Summary: The study highlights that market data do not follow a normal distribution, proposing the use of a mixture distribution and entropic VaR to enhance the reliability of risk management. Simulation experiments on various stocks from real data are conducted to support the findings of this work.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Computer Science, Artificial Intelligence
Zhao-Rong Lai, Cheng Li, Xiaotian Wu, Quanlong Guan, Liangda Fang
Summary: In this study, a novel multitrend conditional value at risk (MT-CVaR) method is proposed for portfolio optimization, incorporating multiple trends and their influences to achieve state-of-the-art investing performance and risk management.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Management
Liao Wang, David D. Yao
Summary: A central problem in planning production capacity is effectively managing demand risk. We integrate capacity planning and risk hedging decisions using the conditional value at risk (CVaR) risk measure. Our model incorporates the impact on demand from a financial asset and includes a dynamic hedging strategy to mitigate demand risk and supplement the payoff. The optimal hedging strategy is found by solving a dual problem and the optimal terminal wealth is derived, resulting in a concave maximization problem for optimizing production quantity.
OPERATIONS RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Souad Chennaf, Jaleleddine Ben Amor
Summary: This paper introduces the concept of entropic value at risk (EVaR) for uncertain random variables and provides formulas for its calculation. It establishes a new mean-EVaR model with uncertain random returns based on this risk criterion. A numerical example is provided to illustrate the applicability of the proposed model. Finally, the mean-EVaR model is compared with the mean-variance model using three types of diversification indices, and the results show that the mean-EVaR model outperforms the mean-variance model in terms of diversification.
Article
Automation & Control Systems
Kevin M. Smith, Margaret P. Chapman
Summary: The standard approach to risk-averse control is to use the exponential utility (EU) and more recently, there has been growing interest in using the conditional value-at-risk (CVaR) for risk-averse control. This study aims to examine the applications of these risk-averse functionals to controller synthesis and safety analysis through numerical examples.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Management
R. Minguez, W. van Ackooij, R. Garcia-Bertrand
Summary: Many practical stochastic optimization problems can be formulated as two-stage stochastic programs, and in situations where risk aversion is of interest, methods such as robust optimization or other risk-functional approaches can be used. This paper focuses on the latter case, particularly when there is a large number of scenarios, proposing a constraint generation algorithm for computational efficiency. The convergence of these algorithms is established and their effectiveness is demonstrated through various numerical experiments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Roy Karasik, Osvaldo Simeone, Hyeryung Jang, Shlomo Shamai Shitz
Summary: This paper presents an optimized layered division multiplexing (LDM) scheme based on conditional value-at-risk (CVaR) rate for ultra-reliable communication scenarios. Meta-learning is introduced to reduce sample complexity, and numerical experiments demonstrate the effectiveness of LDM and the benefits of meta-learning.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Automation & Control Systems
Qichun Zhang, Jianhua Zhang, Hong Wang
Summary: This article presents a new minimum entropy control algorithm for stochastic nonlinear systems subjected to non-Gaussian noises. A new representation of the system stochastic properties is given using the cumulant-generating function based on the moment-generating function. Based on system output and control input samples, a time-variant linear model is identified and the minimum entropy optimization is transformed to system stabilization. An optimal control strategy is developed to achieve randomness attenuation and the boundedness of the controlled system output is analyzed.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Physics, Multidisciplinary
Yi Wang, Qi Sun, Zilu Zhang, Liqing Chen
Summary: By studying the parameters of the multifractal spectrum and their economic significance, a new multifractal measure Rf is constructed to extract price fluctuation information from different levels. Empirical comparisons show that Rf outperforms the conditional value at risk (CVaR) model in risk measurement and investment returns.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Operations Research & Management Science
Juan Li, Bin Xin, Panos M. Pardalos, Jie Chen
Summary: This paper investigates the uncertain stochastic resource allocation problem and proposes bi-objective models to control the risk brought by uncertainties. Two solutions are presented for RAPs and MWTA problems, and two evolutionary algorithms are applied to solve the formulated bi-objective problem. Experimental results show that DMOEA-epsilon C outperforms MOEA/D-AWA on the majority of test instances.
ANNALS OF OPERATIONS RESEARCH
(2021)
Article
Statistics & Probability
Amir Ahmadi-Javid, Asghar Moeini
JOURNAL OF STATISTICAL PLANNING AND INFERENCE
(2019)
Article
Operations Research & Management Science
Amir Ahamdi-Javid, Nasrin Ramshe
4OR-A QUARTERLY JOURNAL OF OPERATIONS RESEARCH
(2019)
Article
Engineering, Environmental
Mariam Ameli, Saeed Mansour, Amir Ahmadi-Javid
RESOURCES CONSERVATION AND RECYCLING
(2019)
Article
Engineering, Industrial
Mohsen Ebadi, Amir Ahmadi-Javid
QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT
(2019)
Article
Management
Amir Ahmadi-Javid, Malihe Fallah-Tafti
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2019)
Article
Statistics & Probability
Mohsen Ebadi, Amir Ahmadi-Javid
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
(2020)
Article
Operations Research & Management Science
Amir Ahmadi-Javid, Nasrin Ramshe
OPTIMIZATION LETTERS
(2020)
Article
Management
Nasrin Ramshe, Amir Ahmadi-Javid
Summary: This paper discusses the importance of congestion control in multi-service network design, proposes a linear programming model, and validates it through a real case study.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2021)
Article
Engineering, Industrial
Amir Ahmadi-Javid, Amir Ardestani-Jaafari
Summary: This paper investigates an unequal area layout problem and develops a flexible bay layout that is robust against future material flow changes. By creating a hybrid algorithm based on Memetic and Simulated Annealing, the proposed heuristic is shown to be efficient and effective through numerical experiments. The study emphasizes the importance of adequately incorporating the material handling system into the layout design phase.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Statistics & Probability
Amir Ahmadi-Javid, Mohsen Ebadi
Summary: This paper examines the economic-statistical design of memory-type statistical control charts and argues that the commonly used formula is not suitable for these charts. By introducing new concepts, the formula can be corrected to achieve more accurate results. A simulation method is proposed as an alternative for estimating the cost function, showing significantly different optimal designs when the objective function is correctly computed.
COMPUTATIONAL STATISTICS
(2021)
Article
Engineering, Industrial
Amir Ahmadi-Javid, Mohsen Ebadi
QUALITY ENGINEERING
(2020)
Article
Operations Research & Management Science
Amir Ahmadi-Javid, Mohammadreza Fathi
Summary: This paper addresses a practical multi-service system design problem by modeling each service type as a stochastic sequence provided by different facilities, which are modeled as open Jackson queueing networks. Three exact solution methods are applied to solve the formulated problem, and a numerical study is conducted to compare these methods. Finally, an online pharmacy is used as an example to demonstrate the applicability of the problem and provide managerial insights.
Article
Computer Science, Interdisciplinary Applications
Amir Ahmadi-Javid, Pooya Hoseinpour
Summary: This paper demonstrates the application of mixed-integer second-order cone programming (MISOCP) in modeling performance metrics of M/G/1 queues, and compares three different MISOCP formulations. These new formulations efficiently solve large-scale test problems and demonstrate their superiority and generality.
INFORMS JOURNAL ON COMPUTING
(2022)
Article
Health Care Sciences & Services
Amir Ahmadi-Javid, Nasrin Ramshe
OPERATIONS RESEARCH FOR HEALTH CARE
(2020)
Article
Management
Amir Ahmadi-Javid, Seyed Hamed Fateminia, Hans Georg Gemuenden
PROJECT MANAGEMENT JOURNAL
(2020)
