An Integrated Framework for Deterministic and Stochastic Optimization

In recent articles we presented a general methodology for finite optimization. The new method, the Nested Partitions (NP) method, combines partitioning, random sampling, a selection of a promising index, and backtracking to create a Markov chain that converges to a global optimum. In this paper we demonstrate, through examples, how the NP method can be applied to solve both deterministic and stochastic finite optimization problems in a unified framework.

• Type: Conference
• Year: 1997
• Where: WSC
• Authors: Leyuan Shi, Sigurdur Ólafsson
• Keywords: Modeling And Simulation, NP Method, Stochastic finite Optimization, WSC 1997, finite Optimization