1,836 research outputs found
Identifying efficient solutions via simulation: myopic multi-objective budget allocation for the bi-objective case
Simulation optimisation offers great opportunities in the design and optimisation of complex systems. In the presence of multiple objectives, there is usually no single solution that performs best on all objectives. Instead, there are several Pareto-optimal (efficient) solutions with different trade-offs which cannot be improved in any objective without sacrificing performance in another objective. For the case where alternatives are evaluated on multiple stochastic criteria, and the performance of an alternative can only be estimated via simulation, we consider the problem of efficiently identifying the Pareto-optimal designs out of a (small) given set of alternatives. We present a simple myopic budget allocation algorithm for multi-objective problems and propose several variants for different settings. In particular, this myopic method only allocates one simulation sample to one alternative in each iteration. This paper shows how the algorithm works in bi-objective problems under different settings. Empirical tests show that our algorithm can significantly reduce the necessary simulation budget
Non-asymptotic confidence bounds for the optimal value of a stochastic program
We discuss a general approach to building non-asymptotic confidence bounds
for stochastic optimization problems. Our principal contribution is the
observation that a Sample Average Approximation of a problem supplies upper and
lower bounds for the optimal value of the problem which are essentially better
than the quality of the corresponding optimal solutions. At the same time, such
bounds are more reliable than "standard" confidence bounds obtained through the
asymptotic approach. We also discuss bounding the optimal value of MinMax
Stochastic Optimization and stochastically constrained problems. We conclude
with a simulation study illustrating the numerical behavior of the proposed
bounds
Optimal computing budget allocation for constrained optimization
Ph.DDOCTOR OF PHILOSOPH
- …