In this paper, we develop a procedure for selecting a supplier. Suppliers are characterized by their lead time, price and quality (random yield). Each purchased item is acceptable with a given probability and independent of the others. We assume the demands are deterministic with no set-up cost and backordering is allowed. For each supplier, an optimal ordering policy is developed. We prove the...

I systems (IDSs) form an important component of IT security architectures, but the low proportion of hackers in the user population severely limits the usefulness of IDSs. Thus, even when the IDS is good, an intrusion signal may not imply that the user is more likely to be a hacker than a normal user. Ignoring the low base rate for the proportion of hackers results in acting on every intrusion ...

A restless multi-armed bandit problem that arises in multichannel opportunistic communications is considered, where channels are modeled as independent and identical Gilbert-Elliot channels and channel state observations are subject to errors. A simple structure of the myopic policy is established under a certain condition on the false alarm probability of the channel state detector. It is show...

This paper is motivated by inventory problems arising in supply chains characterized by continuous replenishment programs based on information exchanged (reviewed) only intermittently between a manufacturing system (supplier) and a customer (retailer). When the replenishment is once-per-period, rather than at any point of time, a well-known result is the optimality of the so-called myopic base-...

We consider the channel access problem in a multi-channel opportunistic communication system with imperfect channel sensing, where the state of each channel evolves as a non independent and identically distributed Markov process. This problem can be cast into a restless multi-armed bandit (RMAB) problem that is intractable for its exponential computation complexity. A natural alternative is to ...

In this paper, we study the problem of adaptive influence maximization in social networks. It has been proved that if the problem satisfies the adaptive submodularity property, then an adaptive greedy policy is guaranteed to provide an (1 − 1/e)-approximation of the optimal policy. Nevertheless, so far such a property has only been verified in the case of the full-adoption feedback model. As ad...

We consider a multi-channel opportunistic communication system where the states of these channels evolve as independent and statistically identical Markov chains (the Gilbert-Elliot channel model). A user chooses one channel to sense and access in each slot and collects a reward determined by the state of the chosen channel. The objective is to design a sensing policy for channel selection to m...

We study dynamic trial-offer markets, in which participants first try a product and later decide whether to purchase it or not. In these markets, social influence and position biases have a greater effect on the decisions taken in the sampling stage than those in the buying stage. We consider a myopic policy that maximizes the market efficiency for each incoming participant, taking into account...

We study the problem of maximizing a stochastic monotone submodular function with respect to a matroid constraint. Our model can capture the effect of uncertainty in different problems, such as cascade effects in social networks, capital budgeting, sensor placement, etc. We study the adaptivity gap the ratio between the values of optimal adaptive and non-adaptive policies and show that it is eq...

This paper addresses the problem of optimal control of robotic sensing systems aimed at autonomous information gathering in scenarios such as environmental monitoring, search and rescue, and surveillance and reconnaissance. The information gathering problem is formulated as a partially observable Markov decision process (POMDP) with a reward function that captures uncertainty reduction. Unlike ...