Minimal time detection of parameter change in a counting process.- Simulation for passage times in non-Markovian networks of queues.- Simulation uses of the exponential distribution.- A probabilistic analysis of Monte Carlo algorithms for a class of counting problems.- An algorithm for solving linear random differential and integral equations.- Growth versus security in a risky investment model.- Queue predictors for stochastic traffic flows control.- Iterative approximations for networks of queues.- Convergence theories of distributed iterative processes: A survey.- Stochastic integer programming: The distribution problem.- The duality between expected utility and penalty in stochastic linear programming.- A feasible solution to dynamic team problems with a common past and application to decentralized dynamic routing.- Stochastic construction of (q,M) problems.- Asymptotically stable solutions to stochastic optimization problems.- On integrated chance constraints.- Algorithms based upon generalized linear programming for stochastic programs with recourse.- On the use of nested decomposition for solving nonlinear multistage stochastic programs.- Contributions to the methodology of stochastic optimization.- A method of feasible directions for solving nonsmooth stochastic programming problems.- A probabilistic analysis of the set packing problem.
Minimal time detection of parameter change in a counting process.- Simulation for passage times in non-Markovian networks of queues.- Simulation uses of the exponential distribution.- A probabilistic analysis of Monte Carlo algorithms for a class of counting problems.- An algorithm for solving linear random differential and integral equations.- Growth versus security in a risky investment model.- Queue predictors for stochastic traffic flows control.- Iterative approximations for networks of queues.- Convergence theories of distributed iterative processes: A survey.- Stochastic integer programming: The distribution problem.- The duality between expected utility and penalty in stochastic linear programming.- A feasible solution to dynamic team problems with a common past and application to decentralized dynamic routing.- Stochastic construction of (q,M) problems.- Asymptotically stable solutions to stochastic optimization problems.- On integrated chance constraints.- Algorithms based upon generalized linear programming for stochastic programs with recourse.- On the use of nested decomposition for solving nonlinear multistage stochastic programs.- Contributions to the methodology of stochastic optimization.- A method of feasible directions for solving nonsmooth stochastic programming problems.- A probabilistic analysis of the set packing problem.
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