Some results on Bellman equations of optimal production control in a stochastic manufacturing system.
Some scheduling problems with past sequence dependent setup times under the effects of nonlinear deterioration and time-dependent learning
This paper studies scheduling problems which include a combination of nonlinear job deterioration and a time-dependent learning effect. We use past sequence dependent (p-s-d) setup times, which is first introduced by Koulamas and Kyparisis [Eur. J. Oper. Res.187 (2008) 1045–1049]. They considered a new form of setup times which depend on all already scheduled jobs from the current batch. Job deterioration and learning co-exist in various real life scheduling settings. By the effects of learning...
Some Shannon-McMillan approximation theorems for Markov chain field on the generalized Bethe tree.
Sorting and cost analysis of reworking items in rejected lots based on non-destructive variable sampling plan.
Spanning trees of locally finite graphs
Special issue: Stochastic Programming in EURO XXII in Prague
(s,S)-type policy for a production inventory problem with limited backlogging and with stockouts
A production inventory problem with limited backlogging and with stockouts is described in a discrete time, stochastic optimal control framework with finite horizon. It is proved by dynamic programming methods that an optimal policy is of (s,S)-type. This means that in every period the policy is completely determined by two fixed levels of the stochastic inventory process considered.
Stability of Nash equilibria in locational games
Stability of queueing network system with two stations and classes.
Stability of queueing networks.
Stability of retrial queues with versatile retrial policy.
Stability of scheduling with random processing times on one machine
We consider a strong NP-hard single-machine scheduling problem with deadlines and minimizing the total weight of late jobs on a single machine (). Processing times are deterministic values or random variables having Erlang distributions. For this problem we study the tolerance to random parameter changes for solutions constructed according to tabu search metaheuristics. We also present a measure (called stability) that allows an evaluation of the algorithm based on its resistance to random parameter...
Statistical analysis of weighted networks.
Statistical-learning control of multiple-delay systems with application to ATM networks
Congestion control in the ABR class of ATM network presents interesting challenges due to the presence of multiple uncertain delays. Recently, probabilistic methods and statistical learning theory have been shown to provide approximate solutions to challenging control problems. In this paper, using some recent results by the authors, an efficient statistical algorithm is used to design a robust, fixed-structure, controller for a high-speed communication network with multiple uncertain propagation...
Steady state and scaling limit for a traffic congestion model
In a general model (AIMD) of transmission control protocol (TCP) used in internet traffic congestion management, the time dependent data flow vector x(t) > 0 undergoes a biased random walk on two distinct scales. The amount of data of each component xi(t) goes up to xi(t)+a with probability 1-ζi(x) on a unit scale or down to γxi(t), 0 < γ < 1 with probability ζi(x) on a logarithmic scale, where ζi depends on the joint state of the system x. We investigate the long time behavior, mean field...
Stochastic algorithms for buffer allocation in reliable production lines.
Stochastic analysis of a three unit standby system.
Stochastic analysis of the departure and quasi-input processes in a versatile single-server queue.
Stochastic Behaviour of a Robot-Safety Device System
Stochastic Inventory Models Involving Variable Lead Time With a Service Level Constraint