capacity and route length restrictions. The algorithm considers a sequence of adjacent solutions obtained by repeatedly … insertion procedure previously developed by the authors. During the course of the algorithm, infeasible solutions are allowed …

develop an algorithm that should remedy this situation. It exploits recent theoretical results from the Stochastic Dominance … the fastest code currently available, an implementation of our algorithm significantly reduces the computational time … required to solve a problem of considerable size. These results indicate that, as a management tool, this algorithm can be …

nonconvex programs of fractional type. In this paper, an algorithm for the numerical solution of these problems is introduced …

-trading algorithm in a finite number of trades. The final market-clearing prices are discovered by this market trading and an efficient …

global warming policies. Because there are typically profound uncertainties in these models, a simulation approach is often …-case performance provides a robust evaluation of the policy. We test our algorithm on a famous integrated model of climate change …

portfolios of credit-sensitive assets such as loans and corporate bonds. Monte Carlo simulation is an important tool for … performing computations in these models. This paper develops, analyzes, and evaluates two simulation algorithms for intensity … Zeevi, stochastic models and simulation.</i> …

Sequential sampling problems arise in stochastic simulation and many other applications. Sampling is used to infer the …, as is common in the literature. <i>This paper was accepted by Assaf Zeevi, stochastic models and simulation.</i> …

simulation experiment. We also show how different definitions of the sample space yield different variants of the LR method, some …