Sharif Digital Repository

The synthetic aperture radar (SAR) is a microwave imaging radar that achieves high resolution while taking advantage of pulse compression technology and the Doppler effect. In typical radar systems, in order to obtain a good azimuth resolution, one should use an antenna with big aperture. However this is not possible in many cases. SAR has overcome this problem by moving the antenna and so making a synthetic aperture. In inverse SAR (ISAR) the radar antenna is static and synthetic aperture is created by the movement of target. Typical SAR imaging aims at the static targets and when the target is moving, it does not operate well. When detecting moving targets by SAR, both radar and target are... 

With the rapid development in the application of nano-micro systems in space propulsion systems, it is necessary to obtain accurate analysis of flow field in these devices. New generation of space missions are usually performed by using a network of small-scale satellites. The mission control of such small-scale satellites requires specialized propulsion systems than produce small propulsive forces of about 1 micro-Newton. The main purpose of the current PhD thesis is analysing the flow field in different nano/micro propulsion systems by using a hybrid Navier-Stokes (NS)-direct simulation Monte Carlo (DSMC) method. Nano/micro propulsion systems experience different rarefaction regimes from... 

There are several algorithms in the literature to solve the problem of finding an optimal path between two points in a region. Such path satisfies certain constraints while optimizing the objective function. There are many factors in building, or finding, such paths in the real world, whose considerations complicate the solution procedure. This led the researchers to seriously consider meta-heuristics to solve the problem. This study hybridizes several suitable and effective meta-heuristic algorithms to solve the routing problem on a given topography. In this hybrid meta-heuristic algorithm an Ant System finds a horizontal path between the two points under considerations on the topography. A... 

Optimization methodologies with an emphasis on turbomachinery applications are of great interest. In the present study, a framework is proposed for the multi-objective optimization of a compressor blade using a coupled approximator and optimizer modules, as a mean for lowering the vast computational costs. The proposed framework consists of three main units: a CFD solver, an approximator unit, and an optimizer module. In this regard, a multi-layer perceptron artificial neural network is used as the approximator module while a multi-objective genetic algorithm, the non-dominated sorting genetic algorithm-NSGA II, is employed as the optimizer unit of the framework. In addition, a commercial... 

Environmental problems and the consequent governmental regulations, has led supply chains into reverse and closed-loop supply chains. Application of problems such as "Vehicle Routing Problem” has diminished in the closed-loop supply chain, and instead of them, the problem of "Vehicle Routing Problem with Deliveries and Pickups" has become more important. On the other hand, tendency of supply chains to running information in the chain in a desired way, has led to grow the attention to establishing policies of “Vendor Managed Inventory". It seems that by tending the supply chains to closed-loop supply chains which are utilizing the policy of "Vendor Managed Inventory", application of problems... 

Path planning is essential for unmanned aerial vehicles (UAVs) to navigate complex and hazardous environments. Many algorithms have been proposed to solve this problem, but heuristic, meta-heuristic, and hybrid algorithms have recently gained attention due to their ability to find approximate solutions quickly. In this thesis, we propose using the Late Acceptance Hill Climbing (LAHC) algorithm for UAV path planning. We compare LAHC's performance to classical and state-of-the-art optimization algorithms, including simulated annealing (SA), grey wolf optimization (GWO), symbiotic organisms search (SOS), and simplified grey wolf optimizer-modified symbiotic organisms search (SGWO-MSOS).... 

By increasing complexity of systems, soft computing including fuzzy computing, evolutionary computing and intelligent computing, have been developing in recent years. Here, we focus on two subjects making use of soft computing. Firstly, we study fuzzy LR linear systems.
We transform the fuzzy linear system into a corresponding linear crisp system and a constrained least squares model. We show that the fuzzy LR system has an exact solution if and only if the corresponding crisp system is compatible (has a solution) and the optimal value of the corresponding least squares problem is equal to zero. In this case, the exact solution is determined by the solutions of the two corresponding...