Sharif Digital Repository

This paper presents design of a typical Guided Flying Vehicle (GFV) using the multidisciplinary design optimization (MDO). The main objectives of this multi-disciplinary design are maximizing the payload’s weight as well as minimizing the miss distance. The main disciplines considered for this design include aerodynamics, dynamic, guidance, control, structure, weight and balance. This design of GFV is applied to three and six Degree of Freedom (DOF) to show comparison of simulation results. The hybrid scheme of optimization algorithm is based on Nelder-Mead Simplex optimization algorithm and Nondominated Sorting Genetic Algorithm II (NSGA II), called Simplex-NSGA II. This scheme is... 

We consider the problem of massive matrix multiplication, which underlies many data analytic applications, in a large-scale distributed system comprising a group of worker nodes. We target the stragglers' delay performance bottleneck, which is due to the unpredictable latency in waiting for slowest nodes (or stragglers) to finish their tasks. We propose a novel coding strategy, named entangled polynomial code, for designing the intermediate computations at the worker nodes in order to minimize the recovery threshold (i.e., the number of workers that we need to wait for in order to compute the final output). We demonstrate the optimality of entangled polynomial code in several cases, and show... 

Modern sensors consist of arrays of detectors specially arranged to enhance precision, capabilities, and field of view (FOV). Sensor arrays can have multiple functionalities, such as the simultaneous detection of position and motion. We use a linear sensor model and develop an optimization method to design an array of photodiodes. Our objective function minimizes bias and variance estimations. We introduce a maximum likelihood technique to approximate and determine the bias caused by measurement errors, and verify our theory by statistically complete simulations. We apply our theory to design an optimal sun sensor. The sensor has a predefined conical FOV, and its accuracy is controlled by a... 

MapReduce and its open source implementation, Hadoop, have gained widespread adoption for parallel processing of big data jobs. Since the number of such big data jobs is also rapidly rising, reducing their energy consumption is increasingly more important to reduce environmental impact as well as operational costs. Prior work by Mashayekhy et al. (IEEE Trans. Parallel Distributed Syst. 26, 2720–2733, 2016), has tackled the problem of energy-aware scheduling of a single MapReduce job but we provide a far more efficient heuristic in this paper. We first model the problem as an Integer Linear Program to find the optimal solution using ILP solvers. Then we present a task-based greedy scheduling... 

In this study, an inventory system consisting of a single product, one supplier, and multiple identical retailers is considered. Each retailer replenishes inventory from the supplier according to the well known (R,Q) policy. Transit times are constant and retailers face independent Poisson demand. The supplier utilizing the retailers' information in decision making for replenishment policy with a given order size starts with m initial batches (of size Q) and places an order in a batch of size Q to an outside source when a new order is placed. In this inventory system, excess demand is backordered, delayed orders are satisfied on a first-come first-serve basis, and no partial shipment is... 

In this paper, a continuous review inventory system is considered in which an order in a batch of size Q is placed immediately after the inventory position reaches R. Transportation time is constant and demands are assumed to be generated by a stationary Poisson process with one unit demand at a time. Demands not covered immediately from the inventory are backordered. In a recent paper, the exact evaluation of batch-ordering policies for two-level inventory systems was derived. This evaluation is based on a recursive procedure for determining the exact policy costs in case of one-for-one replenishment policies. In this paper, we show how this result can be applied to find the optimal... 

Economic production and on-time ordering are among the most important topics related to production and inventory control issues. An economical production needs a comprehensive and precise planning to be implemented in all production stages. To have a controlled and comprehensive planning system, economic order quantity (EOQ) or economic production quantity (EPQ) models are usually used in various production-inventory environments to minimize costs, avoid delays in orders, and achieve high performance. To meet the demands, sometimes a multiperiod production-inventory planning that involves several products requires outsourcing. In this paper, a production-procurement plan that integrates EOQ... 

In this paper a replacement-repair model is developed to study a renewing free replacement warranty (RFRW) for a class of multi-state deteriorating repairable products. After a replacement, the product warranty is renewed. Two parameters affect the manufacturer's decision to minimally repair or replace a failed item: the product deterioration level at the time of failure and the remaining warranty time. We derive an optimal replacement-repair policy to minimise the expected warranty servicing cost per item sold. In the case of a product with two different working states, we are able to explicitly find the optimal values of the replacement-repair parameters using the Adomian decomposition... 

This paper presents a simultaneous methodology for the optimal design of integrated water and energy networks. Heat transfer coefficients are not constant but are related to the velocity of the streams. Pressure drops in heat exchangers and related power costs are considered. The model is a non-convex MINLP (mixed-integer non-linear program) model, in which the objective is to minimize the total annual costs. To accomplish this task, a new superstructure is proposed that follows the energy and mass streams from sources to sinks, enabling us to consider heat exchange between streams in two separate stages of the HENS before and after mixers. Furthermore, heat recovery from wastewater is... 

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... 

In some industries such as the consumable product industry because of small differences between products made by various companies, customer loyalty is directly related to the availability of products required at that time. In other words, in such industries demand cannot be backlogged but can be totally or partly lost. So companies of this group use make-to-stock (MTS) production policy. Therefore, in these supply chains, final product warehouses play a very important role, which will be highlighted by considering the demand uncertainty as it happens in real world, especially in the consumable product industries in which demand easily varies according to the customer's taste variation,... 

It is of fundamental importance to find algorithms obtaining optimal performance for learning of statistical models in distributed and communication limited systems. Aiming at characterizing the optimal strategies, we consider learning of Gaussian Processes (GP) in distributed systems as a pivotal example. We first address a very basic problem: how many bits are required to estimate the inner-products of some Gaussian vectors across distributed machines? Using information theoretic bounds, we obtain an optimal solution for the problem which is based on vector quantization. Two suboptimal and more practical schemes are also presented as substitutes for the vector quantization scheme. In... 

The paper presents a systematic approach to designing an imaging dish for a concentrator photovoltaic (CPV) system to minimize exergy destruction. The designed CPV system uniformly distributes light rays on the receiver (TPV/multi-junction PV) to enhance the conversion technology efficiency and lifetime. To this end, a parametric dish is designed using imaging optics and the numerical solution of a differential equation. Afterward, a Monte Carlo simulation is used to estimate the output energy and exergy of the CPV system with the parametric dish. Finally, an optimization algorithm finds the optimal design parameters to minimize the system's exergy destruction. The optimal design leads to a... 

An algorithm is proposed to optimize the performance of multiphase structures (composites) under elastodynamic loading conditions. The goal is to determine the distribution of material in the structure such that the time-averaged total stored energy of structure is minimized. A penalization strategy is suggested to avoid the checkerboard instability, simultaneously to generate near 0-1 topologies. As a result of this strategy, the solutions of presented algorithm are sufficiently smooth and possess the regularity of H1 function space. A simple method for the continuum adjoint sensitivity analysis of the corresponding PDE-constrained optimization problem is presented. It is general and can be... 

Active components in amplifiers generate noise. Thus, amplifiers too, produce noise at their output and, therefore, increase the input signal to noise ratio. This is an undesirable feature, more particularly when one is dealing with weak input signals already combined with noise. Thus, reducing amplifiers' noise becomes a necessity for some applications. To overcome this problem, one approach consists of improving electronic device technology. Another approach is the use of advanced techniques in designing low noise amplifiers by taking advantage of pulse shapers. Pulse shapers generally consist of calculated filters made of integrator(s) and differentiator(s) that limit properly the... 

This paper presents a long-term dynamic multi-objective model for distributed generation investment. The proposed model optimizes three objectives, namely active losses, costs and environmental emissions and determines the optimal schemes of sizing, sitting of DG units and specially the dynamics of investment over the planning period. The Pareto optimal solutions of the problem are found using a GA algorithm and finally a fuzzy satisfying method is applied to select the optimal solution considering the desires of the planner. The solutions of Pareto optimal front are analyzed to extract general useful information for planners about the appropriate DG technologies and placement schemes. The... 

Permutation and scaling ambiguities are relevant issues in tensor decomposition and source separation algorithms. Although these ambiguities are inevitable when working on real data sets, it is preferred to eliminate these uncertainties for evaluating algorithms on synthetic data sets. As shown in the paper, the existing performance indices for this purpose are either greedy and unreliable or computationally costly. In this paper, we propose a new performance index, called CorrIndex, whose reliability can be proved theoretically. Moreover, compared to previous performance indices, it has a low computational cost. Theoretical results and computer experiments demonstrate these advantages of... 

Designing proper spectrum decision schemes for cognitive radios (CRs) improves spectral usage efficiency as well as CR network throughput. One of the key effecting factors of the CR network throughput is the spectrum sensing sequences of the secondary users (SUs). In this paper, the SUs throughput maximization through appropriately selecting the sensing sequences of the SUs, called sensing matrix (SM), is investigated. More specifically, first the average throughput of the CR network is evaluated for a given SM in the case of error-free channel sensing. Then, an optimization problem is formulated with the aim to maximize the network throughput by finding the optimal SM. In order to avoid... 

In this paper, a seismic reliability-based approach is proposed to design inelastic steel moment frame structures isolated by lead-rubber bearing (LRB) systems. An equivalent two-degree-of-freedom system is assumed in which a bilinear behaviour is assigned to both the superstructure and the base. Furthermore, uncertainties associated with the equivalent superstructure mass, stiffness, and yield properties are taken into account by employing proper probability density functions. The proposed design approach is twofold: 1) Reliability curves that return the key design parameters of the inelastic base-isolated structure including: the period of the superstructure, the target base displacement,... 

In this study, the cost function of the defined system is derived first. Then, we prove this function is convex in the system's base stock level. Finally, based on the convexity of the cost function, the optimal solution for the base stock model is determined. For demonstrating the applicability of the proposed method, we resort to solving an example. © 2009 Asian Network for Scientific Information