Sharif Digital Repository

In this paper, a three-dimensional numerical model is developed to analyze flow characteristics of pressure driven, electroosmotic and combined pressure driven-electroosmotic flows through micro-channels. The governing system of equations consists of the electric-field and flow-field equations. The solution procedure involves three steps. The net charge distribution on the cross section of the microchannel is computed by solving two-dimensional Poisson-Boltzmann equation using the finite element method. Then, using the computed fluid's charge distribution, the magnitude of the resulting body force due to interaction of an external electric field with the charged fluid is calculated along the... 

This paper introduces a novel and practical vendor selection problem of a firm that cooperates with multiple geographically dispersed stores. In this problem, the firm entrusts some of its business process to external vendors, and each store can split the ordered quantity between one or more potential vendors, represented as a multi-sourcing strategies. Moreover, the Cobb–Douglas demand function is utilised to establish a relationship between the market demand and the selling price; representing price-sensitive demand. This paper seeks to choose the best vendors, to allocate the stores to them, and to find the optimal values for inventory-related decisions. The approach is based on the... 

The learning effects of the workers and machine deterioration in an aggregate production planning (APP) problem have not been taken into account in the literature yet. These factors affect the performance of any real-world production system and require attention. In this paper, a bi-objective optimization model is developed for an APP problem with labor learning effect and machine deterioration. The first objective of this model maximizes the profit by improving learning and reducing the failure cost of the system. The second objective function minimizes the costs associated with repairs and deterioration, which depend on the failure rate of the machines in the production periods. The aim of... 

In this study, a single-period two-level inventory control problem is modeled in which the demand is a random variable and shortage is assumed as lost sales. The aim is to maximize the expected profit and the service level at the end of the season, simultaneously. The setting investigated in this research is unique in the sense that both all-units and incremental discount policies are considered under a budget constraint. The developed NP-hard bi-objective optimization problem cannot be solved using an exact method within a reasonable computational time. Thus, a meta-heuristic algorithm, namely multi-objective invasive weeds optimization algorithm (MOIWO) is developed to solve the proposed... 

Control problem in a biological system is the problem of finding an interventional policy for changing the state of the biological system from an undesirable state, e.g. disease, into a desirable healthy state. Boolean networks are utilized as a mathematical model for gene regulatory networks. This paper provides an algorithm to solve the control problem in Boolean networks. The proposed algorithm is implemented and applied on two biological systems: T-cell receptor network and Drosophila melanogaster network. Results show that the proposed algorithm works faster in solving the control problem over these networks, while having similar accuracy, in comparison to previous exact methods. Source... 

A numerical method for solving Fredholm-Volterra Hammerstein integral equations is presented. This method is based on replacement of the unknown function by truncated series of well known Chebyshev expansion of functions.The quadrature formula which we use to calculate integral terms can be estimated by Fast Fourier Transform (FFT). The numerical examples and the number of operations show the advantages of this method to some other usual methods. © 2006 Elsevier Inc. All rights reserved  

This paper presents a new and ubiquitous framework for establishing achievability results in network information theory (NIT) problems. The framework is used to prove various new results. To express the main tool, consider a set of discrete memoryless correlated sources (DMCS). Assume that each source (except one, Z n) is randomly binned at a finite rate. We find sufficient conditions on these rates such that the bin indices are nearly mutually independent of each other and of Z n. This is used in conjunction with the Slepian-Wolf (S-W) result to set up the framework. We begin by illustrating this method via examples from channel coding and rate-distortion (or covering problems). Next, we... 

Here, we refine our recent proposed method for computing a positive definite solution to an overdetermined linear system of equations with multiple right-hand sides. This problem is important in several process control contexts including quadratic models for optimal control. The coefficient and the right-hand side matrices are, respectively, named data and target matrices. In several existing approaches, the data matrix is unrealistically assumed to be error free. We have recently presented an algorithm for solving such a problem considering error in measured data and target matrices. We defined a new error in variables (EIV) error function considering error for the variables, the necessary... 

Since that heuristic state space planners have been very successful in classical planning, this approach is currently the most popular strategy in dealing with temporal planning, too. However, all current state-space temporal planners use a search method known as decision epoch planning, which is not complete for problems with required concurrency. In theory, this flaw can be overcome by employing another search method, called temporally lifted progression planning. In this paper, we show that there are two major problems which, if not tackled properly, can cause the latter method to be very inefficient in practice. The first problem is dealing with the remarkably large state space of... 

Link adaptation of a wireless cellular network is of much attention due to the desire of maximizing both the a erage lin throughput and co erage reliability, which have conflicting effect on each other. In this paper, the intra-cell lin adaptation problem is formulated as a non-differentiable constrained optimization problem to maximize average link throughput while guaranteeing the best possible coverage reliability. To achieve this, a cutting plane optimization algorithm is employed. The performance of our method: adaptive modulation/coding with power management (AMCWPM) using proposed algorithm is compared with that of an adaptive modulation/coding (AMC) with no power management.... 

In this paper, we follow two control tasks in a leader following frame with undirected network and local communications. As the first goal, distributed behavioral imitation, which is necessary to fit agents with complicated motion equations in kinematic frames, is discussed. Providing real agents with behavioral controller makes them capable to act as a kinematic particle. The second goal is to design an active leading strategy for the LA to move the group on a predefined path. Both problems can be mathematically modeled in an affine form, which is the reason behind using a unique adaptive controller to solve them. The controller is based on a neuro-fuzzy structure with critic-based leaning... 

In this paper, an approach is proposed for controlling the uncertain Lorenz system. Based on an identification technique, a controller is designed that guarantees the regulation of all states in the presence of system uncertainty. Since in some applications the challenging problem of output tracking is desired, we have proposed several effective set-point tracking control techniques. The control schemes that are based on the feedback linearization method, can stabilize the internal dynamics of the system. Simulation results have illustrated the effectiveness of the proposed schemes. © 2005 Elsevier Ltd. All rights reserved  

Due to the enlargement and complexity of software systems and the need for maintenance and update, success of systems depends strongly on their architecture. Software architecture has been a key element in software development process in two past decades. Therefore, choosing the correct architecture is a critical issue in software engineering domain, with respect to the extremely extension of architecturedriven designs. Moreover, software architecture selection is a multi-criteria decision-making problem in which different goals and objectives should be considered. In this paper, a Decision Support System (DSS) has been designed which provides software architects with more precise and... 

In a proportional task allocation problem, it is desired for robotic agents to have equal duty to capability ratios. Here, this problem is addressed as a combination of deployment and consensus problems. Tasks occur in a convex region and each task is assigned to its nearest agent. Agents are deployed on this area in order to reach consensus over the value of their duty to capability ratio. A distributed, asynchronous, and scalable algorithm is presented for solving this problem in continuous time domain  

In this research, a new metaheuristic optimization algorithm, inspired by biological nervous systems and artificial neural networks (ANNs) is proposed for solving complex optimization problems. The proposed method, named as neural network algorithm (NNA), is developed based on the unique structure of ANNs. The NNA benefits from complicated structure of the ANNs and its operators in order to generate new candidate solutions. In terms of convergence proof, the relationship between improvised exploitation and each parameter under asymmetric interval is derived and an iterative convergence of NNA is proved theoretically. In this paper, the NNA with its interconnected computing unit is examined... 

The ODYSSEY design methodology has been recently introduced as a viable solution to the increasing design complexity problem in the ASICs. It is an object-oriented design methodology which models a system in terms of its constituting objects and their corresponding method calls. Some of these methods are implemented in hardware; others are simply executed by a general purpose processor. One fundamental element of this methodology is a network on chip that implements method invocation for hardware-based method calls. However this network is prone to faults, thus errors on it may result into system failure. In this paper an architectural fault-tolerance enhancement to the ODYSSEY design... 

The continuing process of software systems enlargement in size and complexity becomes system design extremely important for software production. In this way, the role of software architecture is significantly important in software development. It serves as an evaluation and implementation plan for software development and software evaluation. Consequently, choosing the correct architecture is a critical issue in software engineering domain. Moreover, software architecture selection is a multicriteria decision-making problem in which different goals and objectives must be taken into consideration. In this paper, more precise and suitable decisions in selection of architecture styles have been... 

All realistic Multi-Criteria Decision Making (MCDM) problems face various kinds of uncertainty. Since the evaluations of alternatives with respect to the criteria are uncertain they will be assumed to have stochastic nature. To obtain the uncertain optimism degree of the decision maker fuzzy linguistic quantifiers will be used. Then a new approach for fuzzy-stochastic modeling of MCDM problems will be introduced by merging the stochastic and fuzzy approaches into the OWA operator. The results of the new approach, entitled FSOWA, give the expected value and the variance of the combined goodness measure for each alternative. Robust decision depends on the combined goodness measures of... 

In this paper, we consider the call admission problem in cellular networks that support several classes of calls. In the first part of this paper, we first introduce a multi-threshold guard channel policy and study its limiting behavior under the stationary traffic. Then we give an algorithm for finding the optimal number of guard channels that minimizes the blocking probability of calls with lowest level of QoS subject to constraints on blocking probabilities of other calls. In the second part of the paper, we give an algorithm for finding the minimum number of channels subject to constraints on blocking probabilities of calls. Finally, we propose a prioritized channel assignment algorithm... 

In this paper, we use the generalized regression neural network (GRNN) for the inverse scattering from perfectly conducting cylindrical targets illuminated by the transverse magnetic to z polarization