Article
Environmental Studies
Dani Broitman, Yakov Ben -Haim
Summary: Spatial planning involves uncertainty about the future, and scenario-based forecasting is a common way to address this uncertainty. Combining retrospective analysis with prospective scenario-based forecasting can provide more accurate and useful insights for future decision-making.
Article
Engineering, Civil
Antoine Ajenjo, Emmanuel Ardillon, Vincent Chabridon, Bertrand Iooss, Scott Cogan, Emeline Sadoulet-Reboul
Summary: The main objective of this work is to study the impact of the choice of input uncertainty models on robustness evaluations for probabilities of failure. Aleatory and epistemic uncertainties are jointly propagated by considering hybrid models and applying random set theory. The notion of horizon of uncertainty found in the info-gap method allows to compare the bounds on the probability of failure obtained from different epistemic uncertainty models at increasing levels of uncertainty. Info-gap robustness and opportuneness curves are obtained and compared for various uncertainty models, and a specific demand value is used as a metric to quantify the gain of information on the probability of failure.
Article
Thermodynamics
Yakov Ben-Haim
Summary: Different types of feedback to energy consumers have been studied for reducing energy use, with the challenge being to reliably achieve a specified reduction in energy use due to uncertainty in consumers' responses. This article uses info-gap decision theory to model and manage this uncertainty, showcasing how robustness to uncertainty should be the basis for evaluating feedback programs. The analysis of robustness supports the evaluation and prioritization of alternatives based on confidence in outcomes assessed by robustness.
Article
Computer Science, Interdisciplinary Applications
Xiang Li, Xibing Li, Zilong Zhou, Yonghua Su, Wengui Cao
Summary: This paper introduces a non-probabilistic information-gap approach (IGA) for assessing rock tunnel reliability in the face of severely deficient information on rock properties. The IGA is applied in a typical rock tunnel example to quantify uncertainties and assess reliability through an information-gap model and robustness function constructed to address severe lack of information.
COMPUTERS AND GEOTECHNICS
(2021)
Article
Green & Sustainable Science & Technology
Mashor Housh, Tomer Aharon
Summary: Global climate change challenges traditional practices for planning and managing Water Resources Systems. This study aims to develop a water management model based on Info-Gap Decision Theory to address deep uncertainty, providing a tool for decision-making under unpredictable future conditions.
Article
Green & Sustainable Science & Technology
Shira Daskal, Adar Ben-Eliyahu, Gal Levy, Yakov Ben-Haim, Ronnen Avny
Summary: Despite the uncertainty in earthquake predictions, social-emotional preparedness is crucial for quick recovery of the population. This study aims to develop a robust program and evaluate its effectiveness using info-gap decision theory.
Article
Green & Sustainable Science & Technology
Rahim Fathi, Behrouz Tousi, Sadjad Galvani
Summary: This study introduces a new approach for optimizing and allocating clean renewable energy resources in distribution networks to minimize costs and increase reliability through a risk aversion strategy. Results demonstrate that the scenario of simultaneous wind turbine allocation and network reconfiguration is the most cost-effective option under a 20% uncertainty budget.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Computer Science, Interdisciplinary Applications
C. McPhail, H. R. Maier, S. Westra, L. van der Linden, J. H. Kwakkel
Summary: In order to assist decision making about environmental systems under deep uncertainty, researchers have introduced a generic guidance framework and software package to help identify the most robust decision alternatives. This tackles the difficulty of choosing between robustness metrics and scenarios, providing a consistent and easy-to-use approach to quantify system robustness and make robust decisions.
ENVIRONMENTAL MODELLING & SOFTWARE
(2021)
Article
Management
Aleksandr Pirogov, Evgeny Gurevsky, Andre Rossi, Alexandre Dolgui
Summary: This paper addresses an optimization problem involving machine constraints, cycle time constraints, and task precedence relations, aiming to find the most robust line configuration under task processing time uncertainty. The robustness of a given line configuration is measured by its stability radius, and a mixed-integer linear program method is proposed to solve the problem.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Mathematics, Applied
Evgeny Gurevsky, Andry Rasamimanana, Aleksandr Pirogov, Alexandre Dolgui, Andre Rossi
Summary: This paper addresses an optimization problem of designing a new assembly line considering the constraints of available workstations, cycle time, and task precedence relations. The objective is to find the most robust line configuration that can withstand processing time uncertainty, measured by a new indicator called stability factor. The problem is proven to be strongly NP-hard and upper bounds are proposed. The relation between the stability factor and another robustness indicator, stability radius, is investigated.
DISCRETE APPLIED MATHEMATICS
(2022)
Article
Physics, Particles & Fields
Fabio Briscese, Leonardo Modesto
Summary: We demonstrate that Minkowskian non-local quantum field theories are not unitary, as opposed to the case of Euclidean non-local scalar field which satisfies the Cutkosky rules. The breaking of unitarity in Minkowskian theory is clearly identified.
EUROPEAN PHYSICAL JOURNAL C
(2021)
Article
Automation & Control Systems
Pieter Appeltans, Silviu-Iulian Niculescu, Wim Michiels
Summary: This paper presents an analysis of the stability properties of PID controllers for dynamical systems with multiple state delays. It focuses on the mathematical characterization of the potential sensitivity of stability with respect to small parameter perturbations originating from neglecting feedback delay, a finite-difference approximation of the derivative action, or neglecting fast dynamics. The paper introduces the concept of "strong stability" and proves that it can be achieved by adding a low-pass filter with a sufficiently large cutoff frequency to the control loop, as long as the filter itself does not destabilize the nominal closed loop system. The theoretical results are illustrated by analytical examples, including a third-order unstable system. The paper also provides a computational procedure for designing strongly stabilizing PID controllers.
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
(2022)
Article
Automation & Control Systems
Nguyen Khoa Son, Le Van Ngoc
Summary: This paper investigates the robustness of exponential stability of positive switched systems described by linear functional differential equations under arbitrary or average dwell time switching. It introduces the notion of structured stability radius to measure the stability robustness of the system subject to parameter affine perturbations. It establishes formulas for computing this radius and estimating its lower bounds and upper bounds. The results provide tractably computable formulas or bounds for the stability radius in the case of switched linear systems with multiple discrete time-delays or/and distributed time-delays. The extension of the obtained results to non-positive systems and the class of multi-perturbations is also presented.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Chemistry, Multidisciplinary
Gerardo Iovane, Riccardo Emanuele Landi, Antonio Rapuano, Riccardo Amatore
Summary: Researchers propose a learning model to assess the relevance of probability, plausibility, credibility, and possibility opinions, and test it with a case study on predicting football players' transfer costs. The results demonstrate the model's high performance and importance in decision support systems.
APPLIED SCIENCES-BASEL
(2022)
Article
Management
Xavier Schepler, Andre Rossi, Evgeny Gurevsky, Alexandre Dolgui
Summary: One-dimensional bin-packing is a combinatorial optimization problem, and this paper investigates variants of the problem to address uncertain item sizes. Robust solutions are proposed using stability radius and relative resiliency calculations, with a 0-1 linear programming formulation and branch-and-price algorithm developed for optimal solutions. Experimental results on benchmark sets explore the protection against uncertainty offered by each approach and the cost of robustness.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)