Abstract The performance of stochastic optimisers can be assessed experimentally on given problems by performing multiple optimisation runs, and analysing the results. Since an opt...
Viviane Grunert da Fonseca, Carlos M. Fonseca, And...
In the last decade ordinal optimization (OO) has been successfully applied in many stochastic simulation-based optimization problems (SP) and deterministic complex problems (DCP). ...
To solve a decision problem under uncertainty via stochastic programming means to choose or to build a suitable stochastic programming model taking into account the nature of the r...
This paper studies microprocessor floorplanning considering thermal and throughput optimization. We first develop a stochastic heat diffusion model taking into account the appl...
We present the agent programming language POGTGolog, which combines explicit agent programming in Golog with game-theoretic multi-agent planning in a special kind of partially obs...