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The Distributed Constraint Optimization (DCOP) framework can be used to model a wide range of optimization problems that are inherently distributed. A distributed optimization problem can be viewed as a problem distributed over a set of agents, where agent ...
The paper studies the benefits of multi-path content delivery from a rate-distortion efficiency perspective. We develop an optimization framework for computing transmission schedules for streaming media packets over multiple network paths that maximize the ...
Recently, the optimisation of end-of-life (EOL) product recovery processes has been highlighted. At the inspection phase after disassembly, each part can have various recovery options such as reuse, reconditioning, remanufacturing, and disposal. Depending ...
MPTCP has been proposed recently as a mechanism for sup- porting transparently multiple connections to the applica- tion layer. It is under discussion at the IETF. We show, however, that the current MPTCP suffers from two prob- lems: (P1) Upgrading some TC ...
In this paper, we study the dynamic hybrid berth allocation problem in bulk ports with the objective to minimize the total service times of the vessels. We propose two exact methods based on mixed integer progra mming and generalized set partitionin g, and ...
Adaptive Optics (AO) improves the efficiency of the optical devices in confocal imaging systems by reducing wavefront aberrations. Aberration is caused by imperfections within the system and reduces the optical signal to noise ratio of the resultant images ...
In many situations, agents optimize their own operations locally but their local problems are interdependent. We consider the problem of coordinating these local problems to find a globally optimal solution. We model the coordination problem as a Distribut ...
We consider the assignment of gates to arriving and departing flights at a large hub airport. It is considered to be a highly complex problem even in planning stage when all flight arrivals and departures are assumed to be known precisely in advance. There ...
Summary: NoRSE was developed to analyze high-frequency datasets collected from multistate, dynamic expts., such as mol. adsorption and desorption onto carbon nanotubes. As technol. improves sampling frequency, these stochastic datasets become increasingly ...
The Upper Confidence Bounds (UCB) algorithm is a well-known near-optimal strategy for the stochastic multi-armed bandit problem. Its extensions to trees, such as the Upper Confidence Tree (UCT) algorithm, have resulted in good solutions to the problem of G ...