Sharif Digital Repository

In this paper, we study an adaptive random search method based on continuous action-set learning automaton for solving stochastic optimization problems in which only the noise-corrupted value of function at any chosen point in the parameter space is available. We first introduce a new continuous action-set learning automaton (CALA) and study its convergence properties. Then we give an algorithm for optimizing an unknown function. © 2005 The Franklin Institute. Published by Elsevier Ltd. All rights reserved  

Compute-and-forward is a promising strategy to tackle interference and obtain high rates between the transmitting users in a wireless network. However, the quality of the wireless channels between the users substantially limits the achievable computation rate in such systems. In this paper, we introduce the idea of using intelligent reflecting surfaces (IRSs) to enhance the computing capability of the compute-and-forward systems. For this purpose, we consider a multiple access channel (MAC) where a number of users aim to send data to a base station (BS) in a wireless network, where the BS is interested in decoding a linear combination of the data from different users in the corresponding... 

Taking into account the effect of viscous dissipation in the energy equation, we numerically explore the flow of an incompressible micropolar fluid with heat and mass transfer through a resistive porous medium between plane channel walls. By exploiting a similarity transformation, the governing partial differential equations are transformed into a system of nonlinear coupled ordinary differential equations, which are solved numerically for various problem parameters by means of quasi-linearization. It is found that the effect of viscous dissipation is to increase the heat and mass transfer rate at both the lower and upper walls of the channel. © 2019, Pleiades Publishing, Ltd  

A production-routing problem with price-dependent demand (PRP-PD) is studied in this paper. Demand follows a general convex, differentiable, continuous and strictly decreasing function in price. The problem is modeled as a mixed integer nonlinear program (MINLP). Two Outer Approximation (OA) based algorithms are developed to solve the PRP-PD. The efficiency of the proposed algorithms in comparison with commercial MINLP solvers is demonstrated. The computational results show that our basic OA algorithm outperforms the commercial solvers both in solution quality and in computational time aspects. On the other hand, our extended (two-phase) OA algorithm provides near-optimal solutions very...