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Due to the low costs and energy needed, cyber-physical systems are adopting multi-core processors for their embedded computing requirements. In order to guarantee safety when the application has real-time constraints, a critical requirement is to estimate ...

We consider a dynamic pricing problem in which a firm sells one item to a single buyer to maximize expected revenue. The firm commits to a price function over an infinite horizon. The buyer arrives at some random time with a private value for the item. He ...

In this paper, we study the adaptive submodular cover problem under the worst-case setting. This problem generalizes many previously studied problems, namely, the pool-based active learning and the stochastic submodular set cover. The input of our ...

Many operational settings share the following three features: (i) a centralized planning system allocates tasks to workers or service providers, (ii) the providers generate value by completing the tasks, and (iii) the completion of tasks influences the ...

We consider a search problem on trees in which an agent starts at the root of a tree and aims to locate an adversarially placed treasure, by moving along the edges, while relying on local, partial information. Specifically, each node in the tree holds a ...

Motivated by urban freight transportation practices in China, we study an optimal truck loading problem in which a fixed cost and an additional cost that depends on the number of unloading points are associated with each truck used. The truck loading ...

In “Worst-Case Benefit of Restocking for the Vehicle Routing Problem with Stochastic Demands,” Bertazzi and Secomandi shed new light on an old yet timely problem in transportation. They analyze the benefit of planning replenishment trips in the vehicle ...

The extant literature on the vehicle routing problem with stochastic demands indicates that the restocking strategy yields moderate percentage expected cost reductions relative to the a priori approach but lacks theoretical support for this improvement. ...

We study the problem of developing efficient approaches for proving worst-case bounds of non-deterministic recursive programs. Ranking functions are sound and complete for proving termination and worst-case bounds of non-recursive programs. First, we ...

We study integrated production- and delivery-scheduling problems that arise in practical make-to-order settings in several industries. In these problems, make-to-order products are first processed in a plant and then delivered to customer sites through ...

Consider a central planner with a limited budget charging taxes and allocating copayment subsidies to competing producers of a commodity, with the goal of maximizing its aggregate consumption (for example, the Global Fund trying to increase the ...

We study a subsidies and taxes allocation problem with endogenous market response subject to a budget constraint. The central planner’s objective is to maximize the consumption of a good, and she allocates per-unit copayments and taxes to its producers. ...

This paper presents a novel technique for type-guided worst-case input generation for functional programs. The technique builds on automatic amortized resource analysis (AARA), a type-based technique for deriving symbolic bounds on the resource usage of ...

Adaptive cubic regularization methods have emerged as a credible alternative to linesearch and trust-region for smooth nonconvex optimization, with optimal complexity amongst second-order methods. Here we consider a general/new class of adaptive ...

This article proposes a novel optimization technique of fault-tolerant mixed-criticality multi-core systems with worst-case response time (WCRT) guarantees. Typically, in fault-tolerant multi-core systems, tasks can be replicated or re-executed in order ...

This paper considers the Multidepot Rural Postman Problem, an extension of the classical Rural Postman Problem in which there are several depots instead of only one. The aim is to construct a minimum cost set of routes traversing each required edge of ...

The vehicle routing problem with drones VRPD is inspired by the increasing interest in commercial drone delivery by companies such as Amazon, Google, DHL, and Walmart. In our model, a fleet of m homogeneous trucks each carries k drones with a speed of α ...

Networks are integral parts of modern safety-critical systems and certification demands the provision of guarantees for data transmissions. Deterministic Network Calculus (DNC) can compute a worst-case bound on a data flow's end-to-end delay. Accuracy of ...

Networks are integral parts of modern safety-critical systems and certification demands the provision of guarantees for data transmissions. Deterministic Network Calculus (DNC) can compute a worst-case bound on a data flow's end-to-end delay. Accuracy of ...

The AFDX (Avionics Full DupleX Switched Ethernet) is the backbone network of most recent avionic communication systems. These systems require deterministic buffer dimensioning for certification reasons. As in such systems, static design is often ...

We develop the first approximation algorithm for periodic-review perishable inventory systems with setup costs. The ordering lead time is zero. The model allows for correlated demand processes that generalize the well-known approaches to model dynamic ...

As the sizes of CMOS devices rapidly scale deep into the nanometer range, the manufacture of nanocircuits will become extremely complex and will inevitably introduce more defects, including more transient faults that appear during operation. For this ...