Search results for " optimality"

Approximation through interpolation in nonconvex multiobjective optimization

2011

Probabilistic Selection Approaches in Decomposition-based Evolutionary Algorithms for Offline Data-Driven Multiobjective Optimization

2022

In offline data-driven multiobjective optimization, no new data is available during the optimization process. Approximation models, also known as surrogates, are built using the provided offline data. A multiobjective evolutionary algorithm can be utilized to find solutions by using these surrogates. The accuracy of the approximated solutions depends on the surrogates and approximations typically involve uncertainties. In this paper, we propose probabilistic selection approaches that utilize the uncertainty information of the Kriging models (as surrogates) to improve the solution process in offline data-driven multiobjective optimization. These approaches are designed for decomposition-base…

Projections onto the Pareto surface in multicriteria radiation therapy optimization

2015

Purpose: To eliminate or reduce the error to Pareto optimality that arises in Pareto surface navigation when the Pareto surface is approximated by a small number of plans. Methods: The authors propose to project the navigated plan onto the Pareto surface as a postprocessing step to the navigation. The projection attempts to find a Pareto optimal plan that is at least as good as or better than the initial navigated plan with respect to all objective functions. An augmented form of projection is also suggested where dose–volume histogram constraints are used to prevent that the projection causes a violation of some clinical goal. The projections were evaluated with respect to planning for int…

Approximation method for computationally expensive nonconvex multiobjective optimization problems

2012

On solving computationally expensive multiobjective optimization problems with interactive methods

2014

APROS-NIMBUS: Dynamic Process Simulator and Interactive Multiobjective Optimization in Plant Automation

2013

Abstract Virtual commissioning of chemical plants often involves a dynamic simulator and an optimization method. This paper demonstrates the integration of APROS, a dynamic process simulator and IND-NIMBUS, an interactive multiobjective optimization software. We implement a multiobjective concentration control problem in APROS involving conflicting objectives and employ a decision maker to interact with IND-NIMBUS and express his preference information to finally obtain his most preferred solution. The results of this study show that APROS and IND-NIMBUS can be integrated and an interactive multiobjective optimization method can help the decision maker in exploring trade-offs among conflict…

Asymptotic optimality of myopic information-based strategies for Bayesian adaptive estimation

2016

This paper presents a general asymptotic theory of sequential Bayesian estimation giving results for the strongest, almost sure convergence. We show that under certain smoothness conditions on the probability model, the greedy information gain maximization algorithm for adaptive Bayesian estimation is asymptotically optimal in the sense that the determinant of the posterior covariance in a certain neighborhood of the true parameter value is asymptotically minimal. Using this result, we also obtain an asymptotic expression for the posterior entropy based on a novel definition of almost sure convergence on "most trials" (meaning that the convergence holds on a fraction of trials that converge…

Balanced Asymmetrical Nearly Orthogonal Designs for first and second order effect estimation

2006

Abstract A method for constructing asymmetrical (mixed-level) designs, satisfying the balancing and interaction estimability requirements with a number of runs as small as possible, is proposed in this paper. The method, based on a heuristic procedure, uses a new optimality criterion formulated here. The proposed method demonstrates efficiency in terms of searching time and optimality of the attained designs. A complete collection of such asymmetrical designs with two- and three-level factors is available. A technological application is also presented.

Implementation aspects of interactive multiobjective optimization for modeling environments: The case of GAMS-NIMBUS

2014

Abstract. Interactive multiobjective optimization methods have provided promising results in the literature but still their implementations are rare. Here we introduce a core structure of interactive methods to enable their convenient implementation. We also demonstrate how this core structure can be applied when implementing an interactive method using a modeling environment. Many modeling environments contain tools for single objective optimization but not for interactive multiobjective optimization. Furthermore, as a concrete example, we present GAMS-NIMBUS Tool which is an implementation of the classification-based NIMBUS method for the GAMS modeling environment. So far, interactive met…

On parsing optimality for dictionary-based text compression—the Zip case

2013

Dictionary-based compression schemes are the most commonly used data compression schemes since they appeared in the foundational paper of Ziv and Lempel in 1977, and generally referred to as LZ77. Their work is the base of Zip, gZip, 7-Zip and many other compression software utilities. Some of these compression schemes use variants of the greedy approach to parse the text into dictionary phrases; others have left the greedy approach to improve the compression ratio. Recently, two bit-optimal parsing algorithms have been presented filling the gap between theory and best practice. We present a survey on the parsing problem for dictionary-based text compression, identifying noticeable results …