An algorithm for binary linear chance-constrained problems using IIS
Sign Up to like & getrecommendations! Published in 2019 at "Computational Optimization and Applications"
DOI: 10.1007/s10589-018-00055-9
Abstract: We propose an algorithm based on infeasible irreducible subsystems to solve binary linear chance-constrained problems with random technology matrix. By leveraging on the problem structure we are able to generate good quality upper bounds to… read more here.
Keywords: algorithm binary; constrained problems; linear chance; chance constrained ... See more keywords
Data-Driven Robust Chance Constrained Problems: A Mixture Model Approach
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Optimization Theory and Applications"
DOI: 10.1007/s10957-018-1376-4
Abstract: This paper discusses the mixture distribution-based data-driven robust chance constrained problem. We construct a data-driven mixture distribution-based uncertainty set from the perspective of simultaneously estimating higher-order moments. Then, we derive a reformulation of the data-driven… read more here.
Keywords: constrained problems; chance constrained; data driven; driven robust ... See more keywords
Two Classes of Smooth Objective Penalty Functions for Constrained Problems
Sign Up to like & getrecommendations! Published in 2019 at "Numerical Functional Analysis and Optimization"
DOI: 10.1080/01630563.2018.1554586
Abstract: Abstract This research aims at solving constrained problems by providing two classes of objective penalty functions which respectively approach to a class of exact penalty functions smoothly. Meanwhile, the authors present two algorithms based on… read more here.
Keywords: constrained problems; two classes; classes smooth; penalty ... See more keywords