Sharif Digital Repository

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... 

Recent developments in Non-Volatile Memories (NVMs) have introduced them as an alternative for SRAMs in on-chip caches. Besides the promising features of NVMs, e.g., near-zero leakage power, immunity to radiation-induced particle strike, and higher density, a major drawback of NVM-based caches is their short lifetime due to limited write endurance. This paper first reveals that in L1 caches, the lifetime of data-cache (D-cache) is about 472x shorter than that of instruction-cache (I-cache) due to extreme imbalance write stress between the two. Then, we propose a technique, so-called Alternating Cache Allocation to Conduct Higher Endurance (A-CACHE), to improve the lifetime of... 

An information system network (ISN) can be modeled as a stochastic-flow network (SFN). There are several algorithms to evaluate reliability of an SFN in terms of Minimal Cuts (MCs). The existing algorithms commonly first find all the upper boundary points (called d-MCs) in an SFN, and then determine the reliability of the network using some approaches such as inclusion-exclusion method, sum of disjoint products, etc. However, most of the algorithms have been compared via complexity results or through one or two benchmark networks. Thus, comparing those algorithms through random test problems can be desired. Here, the authors first state a simple improved algorithm. Then, by generating a... 

In this article, a new mixed finite element formulation is presented for the analysis of two-dimensional compressible solids in finite strain regime. A three-field Hu–Washizu functional, with displacement, displacement gradient and stress tensor considered as independent fields, is utilized to develop the formulation in spatial configuration. Certain constraints are imposed on displacement gradient and stress tensor so that they satisfy the required continuity conditions across the boundary of elements. From theoretical standpoint, simplex elements are best suited for the application of continuity constraints. The techniques that are proposed to implement the constraints facilitate their... 

A modified weakly compressible smoothed particle hydrodynamics (WCSPH) is presented, which utilizes consistent discretization schemes for spatial derivatives in the flow equations. Here, each SPH particle is considered as a computational point that represents a specific part of the fluid. To overcome non-physical oscillations that usually arise in standard WCSPH, we modified the mass conservation equation by using a numerical filter. This modification is based on the difference between two discretization schemes used for the term ∇{dot operator}∇Pρ. Furthermore, a new implementation of wall boundary condition in SPH is introduced. This condition is imposed on the pressure of wall boundary... 

Previously, we have proposed a computational model for decision-making in crisis situations called C-RPD (Computational Recognition Primed Decision). In this paper, a software development process customized for Crisis Situations Decision-Making Systems (CSDMSs) is proposed. Agile processes can skillfully manage uncertainty in software requirements and some of their features like incremental development can solve some problems in developing CSDMSs. However, these processes do not provide comprehensive solutions for issues like the lack of enough knowledge about CSDMSs, very rapid changes, urgent need to overcome security challenges, high development unpredictability, and the performance test.... 

The water cycle algorithm (WCA) is a nature-inspired meta-heuristic recently contributed to the community in 2012, which finds its motivation in the natural surface runoff phase in water cycle process and on how streams and rivers flow into the sea. This method has been so far successfully applied to many engineering applications, spread over a wide variety of application fields. In this paper an enhanced discrete version of the WCA (coined as DWCA) is proposed for solving the Symmetric and Asymmetric Traveling Salesman Problem. Aimed at proving that the developed approach is a promising approximation method for solving this family of optimization problems, the designed solver has been... 

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... 

In order to be a powerful tool, finite-element and finite-volume methods must be capable of handling complex flow in complex geometries. In this work, a structured finite volume element method is suitably developed for solving incompressible flow on a collocated grid topology. The method is generally-applicable to arbitrarily shaped elements and orientations and, thus, challenges the potential to unify many of the different grid topologies into a single formulation. The correct estimation of the convec-tive and diffusive flux terms at cell faces remarkably enhances the solution accuracy of the extended formulation. It is shown that the current formulation is enough robust to treat any... 

How can we optimally trade extra computing power to reduce the communication load in distributed computing? We answer this question by characterizing a fundamental tradeoff between computation and communication in distributed computing, i.e., the two are inversely proportional to each other. More specifically, a general distributed computing framework, motivated by commonly used structures like MapReduce, is considered, where the overall computation is decomposed into computing a set of “Map” and “Reduce” functions distributedly across multiple computing nodes. A coded scheme, named “Coded Distributed Computing” (CDC), is proposed to demonstrate that increasing the computation load of the... 

How can we optimally trade extra computing power to reduce the communication load in distributed computing? We answer this question by characterizing a fundamental tradeoff between computation and communication in distributed computing, i.e., the two are inversely proportional to each other. More specifically, a general distributed computing framework, motivated by commonly used structures like MapReduce, is considered, where the overall computation is decomposed into computing a set of “Map” and “Reduce” functions distributedly across multiple computing nodes. A coded scheme, named “coded distributed computing” (CDC), is proposed to demonstrate that increasing the computation load of the... 

A new heuristic filter, called firefly filter, is proposed for state estimation of nonlinear stochastic systems. The new filter formulates the state estimation problem as a stochastic dynamic optimization and utilizes the firefly optimization algorithm to find and track the best estimation. The fireflies search the state space dynamically and are attracted to one other based on the perceived brightness. The performance of the proposed filter is evaluated for a set of benchmarks and the results are compared with the well-known filters like extended Kalman filter and particle filter, showing improvements in terms of estimation accuracy. © 2016 IEEE  

Horizontal Ground Heat Exchangers (HGHE) as a means of exploiting geothermal energy has come to the fore for a few decades. Various analytical and Computational Fluid Dynamics (CFD) methods have been proposed to predict the performance of the HGHEs. The available analytical approaches are fast; however, they are based on various simplifications and assumptions, affecting their accuracy. On the other hand, CFD methods are more accurate, but their computational cost is a burden. Therefore there is an acute need for an accurate and fast method for predicting the long-term performance of HGHEs. To this aim, this study puts forward a novel hybrid analytical-numerical model for predicting the... 

In this paper, a new nonlinear heuristic filter based on the hybridization of an extended Kalman filter and an ant colony estimator is proposed to estimate the states of a nonlinear system. In this filter, a group of virtual ants searches the state space stochastically and dynamically to find and track the best state estimation while the position of each ant is updated at the measurement time using the extended Kalman filter. The performance of the proposed filter is compared with well-known heuristic filters using a nonlinear benchmark problem. The statistical results show that this algorithm is able to provide promising and competitive results. Then, the new filter is tested on a nonlinear... 

In this paper, a new nonlinear heuristic filter based on the hybridization of an extended Kalman filter and an ant colony estimator is proposed to estimate the states of a nonlinear system. In this filter, a group of virtual ants searches the state space stochastically and dynamically to find and track the best state estimation while the position of each ant is updated at the measurement time using the extended Kalman filter. The performance of the proposed filter is compared with well-known heuristic filters using a nonlinear benchmark problem. The statistical results show that this algorithm is able to provide promising and competitive results. Then, the new filter is tested on a nonlinear... 

A novel combination of a multimode project scheduling problem with material ordering, in which material procurements are exposed to the total quantity discount policy is investigated in this paper. The study aims at finding an optimal Pareto frontier for a triple objective model derived for the problem. While the first objective minimizes the makespan of the project, the second objective maximizes the robustness of the project schedule and finally the third objective minimizes the total costs pertaining to renewable and nonrenewable resources involved in a project. Four well-known multi-objective evolutionary algorithms including non-dominated sorting genetic algorithm II (NSGAII), strength... 

In this paper, a new hybrid metaheuristic algorithm based on the scatter search approach is developed to solve the well-known resource-constrained project scheduling problem. This algorithm combines two solutions from scatter search to build a set of precedence feasible activity lists and select some of them as children for the new population. We use the idea presented in the iN forward/backward improvement technique to define two types of schedule, direct and reverse, and the members of the sequential populations change alternately between these two types of schedule. Extensive computational tests were performed on standard benchmark datasets and the results are compared with the best... 

In this paper, a hypoelasto-viscoplastic endochronic model is developed to capture the strain localization phenomena. The elastic response is stated in terms of hypoelastic model and endochronic constitutive equations are stated in unrotated frame of reference. The infinitesimal theory of endochronic plasticity is extended to large strain range on the basis of the additive decomposition of the strain rate tensor and hypoelasticity. Constitutive equations are stated in unrotated frame of reference that greatly simplifies endochronic constitutive relations in finite plasticity and yields the efficiency of the presented algorithm by total uncoupling material and geometrical nonlinearities. An... 

This paper develops an economic production quantity model for a multi-product multi-objective inventory control problem with fuzzy-stochastic demand and backorders. In this model, the annual demand is represented by trapezoidal fuzzy random numbers. The centroid defuzzification and the expected value methods are applied to defuzzify and make decisions in a random environment. In the case where the warehouse space is limited, the Lagrangian relaxation procedure is first employed to determine the optimal order and the maximum backorder quantities of the products such that the total inventory cost is minimized. The optimal solution obtained by the proposed approach is compared with that... 

The standard power flow (PF) equations are nonlinear, and their integration in the optimal PF (OPF) problem leads to a nonconvex hard-to-solve model. To attack the issue, this paper presents a linear PF model wherein real and imaginary parts of nodal voltages are variables. In the model, loads are interpreted via ZIP model including constant impedance, constant current, and constant power components. To preserve linearity of the model, the complex power is represented via a quadratic function of the hosting node voltage. The function coefficients are derived via curve fitting approaches. Since the model is linear, its solution does not need repetition and can be effectively integrated in the...