Sharif Digital Repository

Networks-on-Chip (NoCs for short) are known as the most scalable and reliable on-chip communication architectures for multi-core SoCs with tens to hundreds IP cores. Proper mapping the IP cores on NoC tiles (or assigning threads to cores in chip multiprocessors) can reduce end-to-end delay and energy consumption. While almost all previous works on mapping consider higher priority for the application's flows with higher required bandwidth, a mapping strategy, presented in this paper, is introduced that considers multicast communication flows in addition to the normal unicast flows. To this end, multicast and unicast traffic flows are first characterized in terms of some new metrics which are... 

In this paper, two different hybrid intelligent systems are applied to develop practical soft identifiers for modeling the tool-tissue force as well as the resulted maximum local stress in laparoscopic surgery. To conduct the system identification process, a 2D model of an in vivo porcine liver was built for different probing tasks. Based on the simulation, three different geometric features, i.e. maximum deformation angle, maximum deformation depth and width of displacement constraint of the reconstructed shape of the deformed body are extracted. Thereafter, two different fuzzy inference paradigms are proposed for the identification task. The first identifier is an adaptive co-evolutionary... 

Data streams have some unique properties which make them applicable in precise modeling of many real data mining applications. The most challenging property of data streams is the occurrence of "concept drift". Recurring concepts is a type of concept drift which can be seen in most of real world problems. Detecting recurring concepts makes it possible to exploit previous knowledge obtained in the learning process. This leads to quick adaptation of the learner whenever a concept reappears. In this paper, we propose a learning algorithm called Pool and Accuracy based Stream Classification with some variations, which takes the advantage of maintaining a pool of classifiers to track recurring... 

Multiple sequence alignment (MSA) is one of the basic and important problems in molecular biology. MSA can be used for different purposes including finding the conserved motifs and structurally important regions in protein sequences and determine evolutionary distance between sequences. Aligning several sequences cannot be done in polynomial time and therefore heuristic methods such as genetic algorithms can be used to find approximate solutions of MSA problems. Several algorithms based on genetic algorithms have been developed for this problem in recent years. Most of these algorithms use very complicated, problem specific and time consuming mutation operators. In this paper, we propose a... 

Background: Real-time crash prediction models are often structured as general log-linear categorical models which must be calibrated using an extensive database. However, there is no method to optimally select the number of categories and the values that define the boundaries between categories when representing continuous measures as categorical variables within the log-linear model. This raises the question of how important the calibration is to the safety impacts estimated when using the crash prediction model. In this paper, we examined the impact that the process used to calibrate the crash prediction model has on estimates of safety impacts of a variable speed limit system. Methods:... 

In deregulated power systems, distribution network operators (DNO) are responsible for maintaining the proper operation and efficiency of distribution networks. This is achieved traditionally through specific investments in network components. The event of distributed generation (DG) has introduced new challenges to these distribution networks. The role of DG units must be correctly assessed to optimise the overall operating and investment cost for the whole system. However, the distributed generation owners (DGOs) have different objective functions which might be contrary to the objectives of DNO. This study presents a long-term dynamic multi-objective model for planning of distribution... 

This paper deals with a two-echelon inventory system for a non-repairable item where the system consists of one warehouse and m identical retailers and uses continuous-review (R, Q) ordering policy. To find an effective stocking policy for this system, a mathematical model with the objective of minimizing the total annual inventory investment subject to constraints on the average annual order frequency, expected number of backorders, and budget is formulated. The mathematical model of the problem at hand is shown to be nonlinear integer-programming and hence a parameter-tuned genetic algorithm is proposed to solve it efficiently. A numerical example is provided at the end to illustrate the... 

We describe an intelligent co-simulator for real time production control of a complex flexible manufacturing system (CFMS) having machine and tool flexibility. The manufacturing processes associated with the CFMS are complicated with each operation being possibly done by several machining centers. The co-simulator design approach is built upon the theory of dynamic meta-model based supervisory control with the cooperation of its own embedded intelligent blocks. The system is implemented by coupling of the centralized simulation controller (CSC) and real-time simulator for enforcing dynamic strategies of shop floor control. The posteriori adaptive co-simulator is equipped with a concurrent... 

The efficient scheduling of the independent and sequential tasks on distributed and heterogeneous computing resources within grid computing environments is an NP-complete problem. Therefore, using heuristic approaches to solve the scheduling problem is a very common and also acceptable method in these environments. In this paper, a new task scheduling algorithm based on bee colony optimization approach is proposed. The algorithm uses artificial bees to appropriately schedule the submitted tasks to the grid resources. Applying the proposed algorithm to the grid computing environments, the maximum delay and finish times of the tasks are reduced. Furthermore, the total makespan of the... 

Networks-on-Chip (NoCs for short) are known as the most scalable and reliable on-chip communication architectures for multi-core SoCs with tens to hundreds IP cores. Proper mapping the IP cores on NoC tiles (or assigning threads to cores in chip multiprocessors) can reduce end-to-end delay and energy consumption. While almost all previous works on mapping consider higher priority for the application's flows with higher required bandwidth, a mapping strategy, presented in this paper, is introduced that considers multicast communication flows in addition to the normal unicast flows. To this end, multicast and unicast traffic flows are first characterized in terms of some new metrics which are... 

This paper proposes a hybrid heuristic optimization method based on genetic algorithm and immune systems to maximize the benefits of Distribution Network Operators (DNOs) accrued due to sizing and placement of Distributed Generation (DG) units in distribution networks. The effects of DG units in reducing the reinforcement costs and active power losses of distribution network have been investigated. In the presented method, the integration of DG units in distribution network is done considering both technical and economical aspects. The strength of the proposed method is evaluated by applying it on a small and a realistic large scale distribution network and the results are compared with... 

This paper presents a new solution framework to locate the workstations in the tandem automated guided vehicle (AGV) systems. So far, the research has focused on minimizing the total flow or minimizing the total AGV transitions in each zone. In this paper, we focus on minimizing total cumulative flow among workstations. This objective allocates workstations to an AGV route such that total waiting time of workstations to be supplied by the AGV is minimized. We develop a property which simplifies the available mathematical formulation of the problem. We also develop a heuristic algorithm for the problem. Computational results show that our heuristic could yield very high-quality solutions and... 

In this paper, we present an energy-efficient manycast routing and spectrum assignment (EEM-RSA) algorithm in elastic optical networks supporting cloud computing applications. The proposed EEM-RSA is adapted for both static and dynamic scenarios. First, an integer linear programing formulation is derived for energy-efficient manycasting and spectrum assignment; then, the corresponding heuristic methods are proposed. To reduce the energy consumption, inactive (idle) elements are turned off, and in the proposed energy-efficient manycasting heuristic, the number of activated elements are minimized. The power consumption of network elements is modeled by considering a constant overhead for the... 

Summary Increasing interest in smart grids exhibits its potential benefits for providing reliable, secure, efficient, environmental friendly and sustainable electricity from renewable energy resources. Here, reliability models of four types of renewable and hybrid distributed generation were developed. A fuzzy multi-objective function was suggested for simultaneous optimization of reliability, electricity generation cost, grid loss and voltage profile. This not only considers uncertainty of renewable energy resources but also provides smart generation dispatching. An efficient reliability index consisting of energy and interruption frequency terms was also defined. A novel hybrid heuristic... 

To improve power system reliability, it is important to reduce the amount of curtailed load when a contingency occurs. While comparing the conventional methods in load shedding, this paper presents a new approach based on sensitivity between line flows and bus power injections. The proposed method selects a set of buses for alleviating the overloaded transmission lines. The RBTS, IEEE-RTS79, and IEEE 118-bus test systems are used to examine the applicability of the proposed method. The results obtained are compared with those of global optimization and heuristic approach from the amount of curtailed load and the computational burden points of view. It will be shown that the proposed method... 

The purpose of this paper is to develop a global optimization model, simplification schemes, and a heuristic procedure for the design of a shortcut-enhanced unidirectional loop aisle-network with pick-up and drop-off stations. The objective is to minimize the total loaded and empty trip distances. This objective is the main determinant for the fleet size of the vehicles, which in turn is the driver of the total life-cycle cost of vehicle-based unit-load transport systems. The shortcut considerably reduces the length of the trips while maintaining the simplicity of the system. The global model solves simultaneously for the loop design, stations' locations and shortcut design. We then develop... 

Minimization of operating costs is one of the most important objectives of power system operators. To achieve this goal, several optimization problems such as unit commitment and optimal power flow have been introduced. Historically, in these problems, the transmission network has been considered as a static system, i.e., the ability of transmission lines switching is not modeled. On the other hand, it has been shown that transmission line switching can significantly reduce operating costs by the means of topology modification. However, considering this capability, a large number of binary variables are introduced in the objective function, and as a consequence, the computation time will be... 

Transportation Discrete Network Design Problem (TDNDP) aims at choosing a subset of proposed projects to minimize the users' total travel time with respect to a budget constraint. Because TDNDP is a hard combinatorial problem, recent research has widely addressed heuristic approaches and ignored the exact solution. This paper explores how application of parallel computation can affect the performance of an exact algorithm in TDNDP. First, we show that the Branch-and-Bound (B&B) algorithm, proposed by LeBlanc, is well adapted to a parallel design with synchronized Master-Slave (MS) paradigm. Then, we develop a parallel B&B algorithm and implement it with two search strategies of... 

Chaotic vibrations of a bistable resonator comprised of doubly clamped shallow arch under simultaneous harmonic AC and static DC distributed electrostatic actuation are investigated. A single degree of freedom model obtained by application of the Galerkin decomposition method to the Euler-Bernoulli shallow arch equation is used for the studies. The bistable arch possessing an asymmetric double-well potential is vulnerable to homoclinic chaos at certain values of parameters. We have implemented the Melnikov's method to derive a necessary condition for the initiation of chaos in this type of resonators. Moreover, we have used a heuristic chaos prediction criterion, together with an analytical... 

In this paper, a mathematical formulation is first derived for a homogenous fuzzy series–parallel redundancy allocation problem, where both the system and its subsystems can only take two states of complete perfect and complete failure. Identical redundant components are included in order to achieve desirable system reliability. The components of each subsystem characterized by their cost, weight, and reliability, are purchased from the market under all-unit discount and incremental quantity discount strategies. The goal is to find the optimum combination of the number of components for each subsystem that maximizes the system reliability under total fuzzy cost and weight constraints. An...