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    Considering short-term and long-term uncertainties in location and capacity planning of public healthcare facilities

    , Article European Journal of Operational Research ; Volume 281, Issue 1 , 16 February , 2020 , Pages 152-173 Motallebi Nasrabadi, A ; Najafi, M ; Zolfagharinia, H ; Sharif University of Technology
    Elsevier B.V  2020
    Abstract
    This paper addresses a real-world problem faced by the public healthcare sector. The problem consists of both the patients’ and service provider's requirements (i.e., accessibility vs. costs) for locating healthcare facilities, allocating service units to those facilities, and determining the facilities’ capacities. The main contribution of this study is capturing both short-term and long-term uncertainties at the modelling stage. The queuing theory is incorporated to consider stochastic demand and service time as a short-term uncertainty, as well as a service level measurement. The developed nonlinear model is then converted into a linear model after introducing a new set of decision... 

    Solving fully dynamic bin packing problem for virtual machine allocation in the cloud environment by the futuristic greedy algorithm

    , Article Journal of Intelligent and Fuzzy Systems ; Volume 40, Issue 3 , 2021 , Pages 4737-4760 ; 10641246 (ISSN) Bakhthemmat, A ; Izadi, M ; Sharif University of Technology
    IOS Press BV  2021
    Abstract
    Many scientists apply fully dynamic bin packing problem solving for resource allocation of virtual machines in cloud environments. The goal of problem-solving is to reduce the number of allocated hosts (bins) and virtual machines (items) migration rates for reducing energy consumption. This study demonstrates a greedy futuristic algorithm (proposed algorithm) for fully dynamic bin packaging with an average asymptotic approximation ratio of 1.231, better than other existing algorithms. The proposed algorithm identifies inappropriate local selections using special futuristic conditions to prevent them as much as possible. Eventually, suitable choices determine and discard the improper ones.... 

    Sequential Bayesian estimation of state and input in dynamical systems using output-only measurements

    , Article Mechanical Systems and Signal Processing ; Volume 131 , 2019 , Pages 659-688 ; 08883270 (ISSN) Sedehi, O ; Papadimitriou, C ; Teymouri, D ; Katafygiotis, L. S ; Sharif University of Technology
    Academic Press  2019
    Abstract
    The problem of joint estimation of the state and input in linear time-invariant dynamical systems is revisited proposing novel sequential Bayesian formulations. An appealing feature of the proposed method is the promise it delivers for updating the covariance matrices of the process and measurement noise in a real-time fashion using asymptotic approximations. The proposed method avoids the direct transmission of the input into predictions of the state using a zero-mean Gaussian distribution for the input. This prior distribution aims to eliminate low-frequency drifts from estimations of the state and input. Moreover, the method is outlined in a computational algorithm offering real-time...