Article
Computer Science, Software Engineering
Giacomo Nannicini, Emiliano Traversi, Roberto Wolfler Calvo
Summary: The paper proposes a nested decomposition scheme for infinite-horizon stochastic linear programs, ensuring convergence to a certain confidence level by exploring finite-horizon problems. The algorithm shows high accuracy in solving instances under random generation.
MATHEMATICAL PROGRAMMING COMPUTATION
(2021)
Article
Computer Science, Interdisciplinary Applications
Sakir Karakaya, Gulser Koksal
Summary: This study focuses on a multi-period product-line-mix problem by modeling it as a two-stage stochastic program, considering product interdependencies and uncertainties. Experimental results show that the model can generate higher expected profits for the business when dealing with uncertainties in pricing and production costs.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Mathematics, Applied
Heng Zhang
Summary: This paper proposes a novel adaptive dynamic programming (ADP)-based model-free policy iteration (PI) algorithm to solve an infinite-horizon continuous-time linear quadratic stochastic (LQS) optimal control problem, which includes both control and state variables in the diffusion term of system dynamics. By using Ito's lemma and expectations, a relationship among the state trajectory, control input, and matrices to be solved is described. The ADP-based model-free algorithm is then developed to approximate the optimal control from collected data without requiring information about all system coefficient matrices. Convergence analysis is provided under mild conditions, and numerical examples demonstrate the effectiveness of the proposed algorithm.
JOURNAL OF APPLIED MATHEMATICS AND COMPUTING
(2023)
Article
Computer Science, Interdisciplinary Applications
Shujin Hou, Ying Fan, Bo-Wen Yi
Summary: This paper explores the crucial role of renewable energy in mitigating climate change and the challenges faced in electricity transition planning. Through the development of a new multistage stochastic mixed-integer model, the scalability and computational efficiency issues in model application have been effectively addressed.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Engineering, Industrial
K. Nageswara Reddy, Akhilesh Kumar
Summary: The study presents a two-stage stochastic linear model for a make-to-order hybrid manufacturing-remanufacturing production system to optimize resource utilization and maximize profit. Uncertainty in demand, core returns rate, and yield are considered, with the aim of maximizing resource utilization and profit through optimal inventory and capacity levels. The analysis also presents scenarios where remanufacturing can be a perfect substitute for manufacturing.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Automation & Control Systems
Xueyang Yang, Zhiyong Yu
Summary: This paper investigates a class of coupled forward-backward stochastic differential equations (FBSDEs) on infinite horizon involving time delays and time advancements, and achieves the unique solvability by introducing a randomized Lipschitz condition and a randomized monotonicity condition. The theoretical result is then applied to a linear-quadratic problem of a time-delayed system with random coefficients, leading to an explicit expression of the unique optimal control.
SYSTEMS & CONTROL LETTERS
(2022)
Article
Automation & Control Systems
Yi Ouyang, Seyed Mohammad Asghari, Ashutosh Nayyar
Summary: The paper discusses a decentralized networked control system, showing that optimal decentralized strategies can be found using coupled Riccati recursions when link failure probabilities are below a certain critical threshold. Beyond this threshold, no strategy can achieve finite cost.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Mathematics, Applied
Archis Ghate
Summary: This paper investigates infinite-horizon nonstationary Markov decision processes and proposes two dual-based approaches to overcome the limitations of current methods, achieving convergence and optimality by maintaining approximations and errors of different variables.
SIAM JOURNAL ON OPTIMIZATION
(2023)
Article
Automation & Control Systems
Chenchen Peng, Weihai Zhang
Summary: This article investigates the necessary and sufficient conditions for Pareto optimal solutions in infinite horizon cooperative difference games, transforms the problems and provides applications. The constrained optimal control problems are converted into unconstrained characterization first, based on the maximum principle, necessary conditions are derived, and sufficient conditions for general nonautonomous systems are presented.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Mathematics
Haoran Dai, Jianjun Zhou, Han Li
Summary: This study investigates infinite horizon optimal control problems driven by a class of stochastic delay evolution equations in Hilbert spaces, with an anticipated backward stochastic evolution equation (ABSEE) as the corresponding adjoint equation. By imposing restrictions on the unbounded operator A*, an a priori estimate for the solution to ABSEEs is established, allowing for the application of Ito inequality and avoidance of certain issues. Existence and uniqueness results for linear backward stochastic evolution equations and ABSEEs on infinite horizon are obtained using approximating methods and fixed-point theory, respectively. Furthermore, necessary and sufficient conditions for optimality of the control problem on infinite horizon are established through Pontryagin's maximum principle.
BULLETIN OF THE MALAYSIAN MATHEMATICAL SCIENCES SOCIETY
(2021)
Article
Computer Science, Software Engineering
Stian Backe, Christian Skar, Pedro Crespo del Granado, Ozgu Turgut, Asgeir Tomasgard
Summary: This paper presents the European Model for Power system Investments with Renewable Energy (EMPIRE), which combines short-term operations and long-term planning decisions. The model can be used to analyze energy transition scenarios and plan for energy beyond 2050.
Article
Automation & Control Systems
Lingying Huang, Junfeng Wu, Yilin Mo, Ling Shi
Summary: This article addresses the problem of sensor and actuator placement and proposes a branch-and-bound algorithm to search for solutions. By deriving lower and upper bounds in the search space, a suboptimal solution is obtained and the optimality gap is analyzed. Numerical examples demonstrate the effectiveness of the algorithm, showing significant reduction in iteration numbers and improvement in LQG cost compared to the canonical algorithm.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Automation & Control Systems
Bing-Chang Wang, Jianhui Huang, Ji-Feng Zhang
Summary: This article studies the social optimal control of mean field linear-quadratic-Gaussian models with uncertainty, implementing a robust optimization approach to design a set of decentralized control strategies that are proven to be asymptotically optimal.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Automation & Control Systems
Yueying Liu, Ting Hou
Summary: This paper considers infinite horizon linear-quadratic Nash games for stochastic differential equations with infinite Markovian jumps and (x,u,v)-dependent noise. A necessary and sufficient condition for the existence of a Nash equilibrium is presented in terms of the solvability of a countably infinite set of coupled generalized algebraic Riccati equations under the condition of strong detectability. The mixed H(2)/H(infinity) control is investigated as an important application using the Nash game approach, and an iterative algorithm is proposed to solve the equations, with a numerical simulation demonstrating its efficiency.
ASIAN JOURNAL OF CONTROL
(2021)
Article
Mathematics
Dragos-Patru Covei
Summary: This article focuses on a stochastic production planning problem with regime switching, aiming to minimize production costs through the value function approach. The main contribution is the identification of an exact solution of an elliptic system of partial differential equations that characterizes the optimal production. A verification result is provided for the determined solution.
Article
Engineering, Industrial
Matias Siebert, Kelly Bartlett, Haejoong Kim, Shabbir Ahmed, Junho Lee, Dima Nazzal, George Nemhauser, Joel Sokol
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2018)
Article
Computer Science, Software Engineering
Alfredo Torrico, Shabbir Ahmed, Alejandro Toriello
MATHEMATICAL PROGRAMMING
(2018)
Article
Computer Science, Software Engineering
Weijun Xie, Shabbir Ahmed
MATHEMATICAL PROGRAMMING
(2018)
Article
Energy & Fuels
Muhammad Zafar, M. Shakil, Shabbir Ahmed, Muhammad Raza-ur-Rehman Hashmi, M. A. Choudhary, Naeem-ur-Rehman
Article
Engineering, Electrical & Electronic
Beste Basciftci, Shabbir Ahmed, Nagi Z. Gebraeel, Murat Yildirim
IEEE TRANSACTIONS ON POWER SYSTEMS
(2018)
Article
Engineering, Electrical & Electronic
Weijun Xie, Shabbir Ahmed
IEEE TRANSACTIONS ON POWER SYSTEMS
(2018)
Article
Computer Science, Software Engineering
Shabbir Ahmed, Weijun Xie
MATHEMATICAL PROGRAMMING
(2018)
Article
Green & Sustainable Science & Technology
Martin N. Hjelmeland, Jikai Zou, Arild Helseth, Shabbir Ahmed
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2019)
Article
Engineering, Electrical & Electronic
Ali Irfan Mahmutogullari, Shabbir Ahmed, Ozlem Cavus, M. Selim Akturk
IEEE TRANSACTIONS ON POWER SYSTEMS
(2019)
Article
Management
Weijun Xie, Shabbir Ahmed
OPERATIONS RESEARCH
(2020)
Article
Management
Ragheb Rahmaniani, Shabbir Ahmed, Teodor Gabriel Crainic, Michel Gendreau, Walter Rei
OPERATIONS RESEARCH
(2020)
Article
Computer Science, Interdisciplinary Applications
Yan Deng, Shabbir Ahmed, Siqian Shen
INFORMS JOURNAL ON COMPUTING
(2018)
Article
Operations Research & Management Science
Lluis-Miquel Munguia, Shabbir Ahmed, David A. Bader, George L. Nemhauser, Yufen Shao
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
(2018)
Proceedings Paper
Computer Science, Artificial Intelligence
Elias B. Khalil, Bistra Dilkina, George L. Nemhauser, Shabbir Ahmed, Yufen Shao
PROCEEDINGS OF THE TWENTY-SIXTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE
(2017)
Article
Computer Science, Interdisciplinary Applications
Lluis-Miquel Munguia, Shabbir Ahmed, David A. Bader, George L. Nemhauser, Vikas Goel, Yufen Shao
COMPUTERS & OPERATIONS RESEARCH
(2017)
Review
Management
Vinicius N. Motta, Miguel F. Anjos, Michel Gendreau
Summary: This survey presents a review of optimization approaches for the integration of demand response in power systems planning and highlights important future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Philipp Schulze, Armin Scholl, Rico Walter
Summary: This paper proposes an improved branch-and-bound algorithm, R-SALSA, for solving the simple assembly line balancing problem, which performs well in balancing workloads and providing initial solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Roshan Mahes, Michel Mandjes, Marko Boon, Peter Taylor
Summary: This paper discusses appointment scheduling and presents a phase-type-based approach to handle variations in service times. Numerical experiments with dynamic scheduling demonstrate the benefits of rescheduling.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Oleg S. Pianykh, Sebastian Perez, Chengzhao Richard Zhang
Summary: Efficient scheduling is crucial for optimizing resource allocation and system performance. This study focuses on critical utilization and efficient scheduling in discrete scheduling systems, and compares the results with classical queueing theory.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Review
Management
Hamed Jahani, Babak Abbasi, Jiuh-Biing Sheu, Walid Klibi
Summary: Supply chain network design is a large and growing area of research. This study comprehensively surveys and analyzes articles published from 2008 to 2021 to detect and report financial perspectives in SCND models. The study also identifies research gaps and offers future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Patrick Healy, Nicolas Jozefowiez, Pierre Laroche, Franc Marchetti, Sebastien Martin, Zsuzsanna Roka
Summary: The Connected Max-k-Cut Problem is an extension of the well-known Max-Cut Problem, where the objective is to partition a graph into k connected subgraphs by maximizing the cost of inter-partition edges. The researchers propose a new integer linear program and a branch-and-cut algorithm for this problem, and also use graph isomorphism to structure the instances and facilitate their resolution. Extensive computational experiments show that, if k > 2, their approach outperforms existing algorithms in terms of quality.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Victor J. Espana, Juan Aparicio, Xavier Barber, Miriam Esteve
Summary: This paper introduces a new methodology based on the machine learning technique MARS for estimating production functions that satisfy classical production theory axioms. The new approach overcomes the overfitting problem of DEA through generalized cross-validation and demonstrates better performance in reducing mean squared error and bias compared to DEA and C2NLS methods.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Stefano Nasini, Rabia Nessah
Summary: In this paper, the authors investigate the impact of time flexibility in job scheduling, showing that it can significantly affect operators' ability to solve the problem efficiently. They propose a new methodology based on convex quadratic programming approaches that allows for optimal solutions in large-scale instances.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Zhiqiang Liao, Sheng Dai, Timo Kuosmanen
Summary: Nonparametric regression subject to convexity or concavity constraints is gaining popularity in various fields. The conventional convex regression method often suffers from overfitting and outliers. This paper proposes the convex support vector regression method to address these issues and demonstrates its advantages in prediction accuracy and robustness through numerical experiments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Kuo-Hao Chang, Ying-Zheng Wu, Wen-Ray Su, Lee-Yaw Lin
Summary: The damage and destruction caused by earthquakes necessitates the evacuation of affected populations. Simulation models, such as the Stochastic Pedestrian Cell Transmission Model (SPCTM), can be utilized to enhance disaster and evacuation management. The analysis of SPCTM provides insights for government officials to formulate effective evacuation strategies.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Qinghua Wu, Mu He, Jin-Kao Hao, Yongliang Lu
Summary: This paper studies a variant of the orienteering problem known as the clustered orienteering problem. In this problem, customers are grouped into clusters and a profit is associated with each cluster, collected only when all customers in the cluster are served. The proposed evolutionary algorithm, incorporating a backbone-based crossover operator and a destroy-and-repair mutation operator, outperforms existing algorithms on benchmark instances and sets new records on some instances. It also demonstrates scalability on large instances and has shown superiority over three state-of-the-art COP algorithms. The algorithm is also successfully applied to a dynamic version of the COP considering stochastic travel time.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Bjorn Bokelmann, Stefan Lessmann
Summary: Estimating treatment effects is an important task for data analysts, and uplift models provide support for efficient allocation of treatments. However, evaluating uplift models is challenging due to variance issues. This paper theoretically analyzes the variance of uplift evaluation metrics, proposes variance reduction methods based on statistical adjustment, and demonstrates their benefits on simulated and real-world data.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Congzheng Liu, Wenqi Zhu
Summary: This paper proposes a feature-based non-parametric approach to minimizing the conditional value-at-risk in the newsvendor problem. The method is able to handle both linear and nonlinear profits without prior knowledge of the demand distribution. Results from numerical and real-life experiments demonstrate the robustness and effectiveness of the approach.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Laszlo Csato
Summary: This paper compares the performance of the eigenvalue method and the row geometric mean as two weighting procedures. Through numerical experiments, it is found that the priorities derived from the two eigenvectors in the eigenvalue method do not always agree, while the row geometric mean serves as a compromise between them.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Guowei Dou, Tsan-Ming Choi
Summary: This study investigates the impact of channel relationships between manufacturers on government policies and explores the effectiveness of positive incentives versus taxes in increasing social welfare. The findings suggest that competition may be more effective in improving sustainability and social welfare. Additionally, government incentives for green technology may not necessarily enhance sustainability.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)