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Inexact direct-search methods for bilevel optimization problems
In this work, we introduce new direct-search schemes for the solution of bilevel optimization (BO) problems. Our methods rely on a fixed accuracy...
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Retraction-Based Direct Search Methods for Derivative Free Riemannian Optimization
Direct search methods represent a robust and reliable class of algorithms for solving black-box optimization problems. In this paper, the application...
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Bilevel Nash Equilibrium Problems: Numerical Approximation Via Direct-Search Methods
We address the numerical approximation of bilevel problems where a Nash equilibrium has to be determined both in the upper level and in the lower...
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Convergence of derivative-free nonmonotone Direct Search Methods for unconstrained and box-constrained mixed-integer optimization
This paper presents a class of nonmonotone Direct Search Methods that converge to stationary points of unconstrained and boxed constrained...
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On polling directions for randomized direct-search approaches: application to beam angle optimization in intensity-modulated proton therapy
Deterministic direct-search methods have been successfully used to address real-world challenging optimization problems, including the beam angle...
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Expected complexity analysis of stochastic direct-search
This work presents the convergence rate analysis of stochastic variants of the broad class of direct-search methods of directional type. It...
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Direct Methods for Constrained Optimization
As we have already seen in Chap. 9 , the direct methods for unconstrained optimization do not use...
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Constructive and Destructive Methods in Heuristic Search
Constructive methods are one of the main families of heuristic approaches to combinatorial optimization problems. They usually start from an empty...
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Local convergence of primal–dual interior point methods for nonlinear semidefinite optimization using the Monteiro–Tsuchiya family of search directions
The recent advance of algorithms for nonlinear semidefinite optimization problems (NSDPs) is remarkable. Yamashita et al. first proposed a...
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Tabu Search
Tabu search is a meta-heuristic that guides a local heuristic search procedure to explore the solution space beyond local optimality. One of the main...
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Worst-Case Complexity Bounds of Directional Direct-Search Methods for Multiobjective Optimization
Direct Multisearch is a well-established class of algorithms, suited for multiobjective derivative-free optimization. In this work, we analyze the...
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Direct Methods for Unconstrained Optimization
Consider the problem
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Stochastic Optimization Methods
This chapter introduces some methods aimed at solving difficult optimization problems arising in many engineering fields. By difficult optimization...
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Development of DIRECT-Type Algorithms
The deterministic derivative-free DIRECT-type algorithms have gained significant recognition in the optimization community due to their simplicity...
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A projected-search interior-point method for nonlinearly constrained optimization
This paper concerns the formulation and analysis of a new interior-point method for constrained optimization that combines a shifted primal-dual...
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Stochastic mesh adaptive direct search for blackbox optimization using probabilistic estimates
We present a stochastic extension of the mesh adaptive direct search (MADS) algorithm originally developed for deterministic blackbox optimization....
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Perfect state transfer, equitable partition and continuous-time quantum walk based search
In this paper, we consider a continuous-time quantum walk based search algorithm. We discuss equitable partition of the graph and perfect state...
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On the use of polynomial models in multiobjective directional direct search
Polynomial interpolation or regression models are an important tool in Derivative-free Optimization, acting as surrogates of the real function. In...
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Analyses of Political Crisis Impact on Tourism: A Panel Counterfactual Approach with Internet Search Index
Existing research has shown that political crisis events can directly impact the tourism industry. However, the current methods suffer from potential...
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Linewalker: line search for black box derivative-free optimization and surrogate model construction
This paper describes a simple, but effective sampling method for optimizing and learning a discrete approximation (or surrogate) of a...
