Search results for " OPTIMA"
showing 10 items of 220 documents
A randomized multicentre trial to compare revascularization with optimal medical therapy for the treatment of chronic total coronary occlusions
2018
Aims: The clinical value of percutaneous coronary intervention (PCI) for chronic coronary total occlusions (CTOs) is not established by randomized trials. This study should compare the benefit of PCI vs. optimal medical therapy (OMT) on the health status in patients with at least one CTO.Method and results: Three hundred and ninety-six patients were enrolled in a prospective randomized, multicentre, open-label, and controlled clinical trial to compare the treatment by PCI with OMT with a 2:1 randomization ratio. The primary endpoint was the change in health status assessed by the Seattle angina questionnaire (SAQ) between baseline and 12 months follow-up. Fifty-two percent of patients have …
Management strategies in patients affected by chronic total occlusions: results from the Italian Registry of Chronic Total Occlusions
2015
Background Through contemporary literature, the optimal strategy to manage coronary chronic total occlusions (CTOs) remains under debate. Objectives The aim of the Italian Registry of Chronic Total Occlusions (IRCTO) was to provide data on prevalence, characteristics, and outcome of CTO patients according to the management strategy. Methods The IRCTO is a prospective real world multicentre registry enrolling patients showing at least one CTO. Clinical and angiographic data were collected independently from the therapeutic strategy [optimal medical therapy (MT), percutaneous coronary intervention (PCI), or coronary artery bypass grafting (CABG)]; a comparative 1-year clinical followup was pe…
Constructing a Pareto front approximation for decision making
2011
An approach to constructing a Pareto front approximation to computationally expensive multiobjective optimization problems is developed. The approximation is constructed as a sub-complex of a Delaunay triangulation of a finite set of Pareto optimal outcomes to the problem. The approach is based on the concept of inherent nondominance. Rules for checking the inherent nondominance of complexes are developed and applying the rules is demonstrated with examples. The quality of the approximation is quantified with error estimates. Due to its properties, the Pareto front approximation works as a surrogate to the original problem for decision making with interactive methods. Qc 20120127
Interactive Multiobjective Robust Optimization with NIMBUS
2018
In this paper, we introduce the MuRO-NIMBUS method for solving multiobjective optimization problems with uncertain parameters. The concept of set-based minmax robust Pareto optimality is utilized to tackle the uncertainty in the problems. We separate the solution process into two stages: the pre-decision making stage and the decision making stage. We consider the decision maker’s preferences in the nominal case, i.e., with the most typical or undisturbed values of the uncertain parameters. At the same time, the decision maker is informed about the objective function values in the worst case to support her/him to make an informed decision. To help the decision maker to understand the behavio…
Shaping communities of local optima by perturbation strength
2017
Recent work discovered that fitness landscapes induced by Iterated Local Search (ILS) may consist of multiple clusters, denoted as funnels or communities of local optima. Such studies exist only for perturbation operators (kicks) with low strength. We examine how different strengths of the ILS perturbation operator affect the number and size of clusters. We present an empirical study based on local optima networks from NK fitness landscapes. Our results show that a properly selected perturbation strength can help overcome the effect of ILS getting trapped in clusters of local optima. This has implications for designing effective ILS approaches in practice, where traditionally only small per…
A Simple Indicator Based Evolutionary Algorithm for Set-Based Minmax Robustness
2018
For multiobjective optimization problems with uncertain parameters in the objective functions, different variants of minmax robustness concepts have been defined in the literature. The idea of minmax robustness is to optimize in the worst case such that the solutions have the best objective function values even when the worst case happens. However, the computation of the minmax robust Pareto optimal solutions remains challenging. This paper proposes a simple indicator based evolutionary algorithm for robustness (SIBEA-R) to address this challenge by computing a set of non-dominated set-based minmax robust solutions. In SIBEA-R, we consider the set of objective function values in the worst c…
Interactive multiobjective optimization with NIMBUS for decision making under uncertainty
2013
We propose an interactive method for decision making under uncertainty, where uncertainty is related to the lack of understanding about consequences of actions. Such situations are typical, for example, in design problems, where a decision maker has to make a decision about a design at a certain moment of time even though the actual consequences of this decision can be possibly seen only many years later. To overcome the difficulty of predicting future events when no probabilities of events are available, our method utilizes groupings of objectives or scenarios to capture different types of future events. Each scenario is modeled as a multiobjective optimization problem to represent differe…
A new preference handling technique for interactive multiobjective optimization without trading-off
2015
Because the purpose of multiobjective optimization methods is to optimize conflicting objectives simultaneously, they mainly focus on Pareto optimal solutions, where improvement with respect to some objective is only possible by allowing some other objective(s) to impair. Bringing this idea into practice requires the decision maker to think in terms of trading-off, which may limit the ability of effective problem solving. We outline some drawbacks of this and exploit another idea emphasizing the possibility of simultaneous improvement of all objectives. Based on this idea, we propose a technique for handling decision maker’s preferences, which eliminates the necessity to think in terms of t…
Functional A Posteriori Error Estimates for Time-Periodic Parabolic Optimal Control Problems
2015
This article is devoted to the a posteriori error analysis of multiharmonic finite element approximations to distributed optimal control problems with time-periodic state equations of parabolic type. We derive a posteriori estimates of the functional type, which are easily computable and provide guaranteed upper bounds for the state and co-state errors as well as for the cost functional. These theoretical results are confirmed by several numerical tests that show high efficiency of the a posteriori error bounds. peerReviewed
Error Estimates for a Class of Elliptic Optimal Control Problems
2016
In this article, functional type a posteriori error estimates are presented for a certain class of optimal control problems with elliptic partial differential equation constraints. It is assumed that in the cost functional the state is measured in terms of the energy norm generated by the state equation. The functional a posteriori error estimates developed by Repin in the late 1990s are applied to estimate the cost function value from both sides without requiring the exact solution of the state equation. Moreover, a lower bound for the minimal cost functional value is derived. A meaningful error quantity coinciding with the gap between the cost functional values of an arbitrary admissible …