Near-optimal solutions of convex semi-infinite programs via targeted sampling

DOI10.1007/s10479-022-04810-4OpenAlexW4286218477MaRDI QIDQ2095909

Souvik Das, Debasish Chatterjee, Ashwin Aravind, Ashish Cherukuri

Publication date: 15 November 2022

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-022-04810-4

zbMATH Keywords

global optimizationconvexitysemi-infinite programmingtargeted sampling

Mathematics Subject Classification ID

Convex programming (90C25) Monte Carlo methods (65C05) Numerical optimization and variational techniques (65K10) Semi-infinite programming (90C34) Applications of functional analysis in optimization, convex analysis, mathematical programming, economics (46N10)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• An inexact primal-dual algorithm for semi-infinite programming
• Thermodynamical approach to the travelling salesman problem: An efficient simulation algorithm
• The CoMirror algorithm with random constraint sampling for convex semi-infinite programming
• Semi-infinite programming
• A semi-infinite programming model for earliness/tardiness production planning with simulated annealing
• Recent contributions to linear semi-infinite optimization: an update
• Uncertain convex programs: randomized solutions and confidence levels
• Robust optimization-methodology and applications
• Stochastic global optimization.
• On the convergence rate of the simulated annealing algorithm
• A New Exchange Method for Convex Semi-Infinite Programming
• Theory and Applications of Robust Optimization
• Semi-Infinite Programming: Theory, Methods, and Applications
• The Exact Feasibility of Randomized Solutions of Uncertain Convex Programs
• Cooling Schedules for Optimal Annealing
• Rates of Convergence for Stochastic Approximation Type Algorithms
• Direct theorems in semi-infinite convex programming
• Convergence theorems for a class of simulated annealing algorithms on ℝ^d
• An algorithm of successive minimization in convex programming
• Introduction to the Scenario Approach
• Scenario Approach for Minmax Optimization with Emphasis on the Nonconvex Case: Positive Results and Caveats
• Point-to-Set Maps in Mathematical Programming
• Discretization in semi-infinite programming: the rate of convergence

This page was built for publication: Near-optimal solutions of convex semi-infinite programs via targeted sampling