Abstract. We study two-stage, finite-scenario stochastic versions of several combinatorial optimization problems, and provide nearly tight approximation algorithms for them. Our pr...
We present an explicit construction of codes that can be list decoded from a fraction (1 - ) of errors in sub-exponential time and which have rate / logO(1) (1/). This comes close...
Abstract—A number of population based optimization algorithms have been proposed in recent years to solve unconstrained and constrained single and multi-objective optimization pr...
Hemant K. Singh, Amitay Isaacs, Trung Thanh Nguyen...
Abstract— This paper presents a new efficient multiobjective evolutionary algorithm for solving computationallyintensive optimization problems. To support a high degree of parall...
Anna Syberfeldt, Henrik Grimm, Amos Ng, Robert Ivo...
Abstract. We study the implementation on grid systems of an efficient algorithm for demanding global optimization problems. Specifically, we consider problems arising in the geneti...