Improving High-dimensional Simulation-driven Optimization

Simulation-Based Optimization for Improving Hospital Performance

Background and Objectives: Nowadays health services affect a significant part of social, economic and political parts of each country. In this case, hospitals are considered as the important and final stage of health service supply chain. Consequently, quality of health services offered by hospitals has a straight impact on the safety of individuals. Methods: </st...

Speeding up COMPASS for high-dimensional discrete optimization via simulation

The convergent optimization via most promising area stochastic search (COMPASS) algorithm is a locally convergent randomsearch algorithm for solving discrete optimization via simulation problems. COMPASS has drawn a significant amount of attention since its introduction. While the asymptotic convergence of COMPASS does not depend on the problem dimension, the finite-time performance of the algo...

Model enhancement: Improving theoretical optimization with simulation

When using optimization techniques based on mathematical models, we often need to make important simplifications. The solution thus provided, even if proven to be theoretically one of the best, might not be so good in practice. Simulation can be used to evaluate the actual performance of the solution. We propose here a coupling between optimization and simulation that tries to improve the solut...

Simulation Optimization: Improving decisions under uncertainty

Head-Driven Simulation of Water Supply Networks

Up to now most of the existing water supply network analyses have been based on demand-driven simulation models. These models assume that nodal outflows are fixed and are always available. However, this method of simulation neglects the pressure-dependent nature of demand that is characterized by changes in actual nodal outflows particularly during critical events like major mechanical or hydra...