Sharif Digital Repository

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 Newsboy problem has always been an important issue in inventory management. The multi-product newsboy problem with random yield and budget constraint named as the Gardener Problem is one of the novels and popular extensions of the newsboy problem. Different from the existing studies, this paper presents a multi-product gardener problem with reservation policy. Moreover, a discount rate is offered to those customers who are willing to make reservations. In addition to the demand from the original customers, extra demand is included in the model due to the motivation received by the discount rate. A solution algorithm namely the multi-product gardener problem with reservation policy... 

The great share of interruptions in distribution networks motivates distribution decision makers to establish various reliability enhancement strategies. Amongst, deploying remote controlled switch (RCS) can make a crucial contribution to the reduction of interruption costs. Nevertheless, the stochastic nature of contingencies affects the RCS worth and imposes substantial financial risk to RCS deployment projects. This paper proposes a mathematical model to consider the risk in the optimal RCS deployment problem. The model determines the number and location of RCSs such that the expected profit is maximized while financial risk is minimized. The risk is modeled through conditional... 

Additive manufacturing (AM), is a new technology for the manufacturing of the physical parts through an additive manner. In the AM process, the orientation pattern of the part is an important variable that significantly influences the product properties such as the build time, the surface roughness, the mechanical strength, the wrinkling, and the amount of support material. The build time and the surface roughness are the more important criteria than others that can be considered to find the optimum orientation of parts. The designers and manufacturing engineers usually attempt to find an optimum solution to reach the product with high quality at the minimum time. Determining the optimum... 

This letter investigates the problem of sparse signal recovery in the presence of additive impulsive noise. The heavy-tailed impulsive noise is well modeled with stable distributions. Since there is no explicit formula for the probability density function of SαS distribution, alternative approximations are used, such as, generalized Gaussian distribution, which imposes ℓp-norm fidelity on the residual error. In this letter, we exploit a continuous mixed norm (CMN) for robust sparse recovery instead of ℓp-norm. We show that in blind conditions, i.e., in the case where the parameters of the noise distribution are unknown, incorporating CMN can lead to near-optimal recovery. We apply... 

In real applications of hub networks, the travel times may vary due to traffic, climate conditions, and land or road type. To facilitate this difficulty, in this paper, the travel times are assumed to be characterized by trapezoidal fuzzy variables to present a fuzzy capacitated single allocation p-hub centre transportation (FCSApHCP) with uncertain information. The proposed FCSApHCP is redefined into its equivalent parametric integer non-linear programming problem using credibility constraints. The aim is to determine the location of p capacitated hubs and the allocation of centre nodes to them in order to minimize the maximum travel time in a hub-and-centre network under uncertain... 

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... 

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... 

For a moving camera recognizing that it has seen a place before now, is one the most important issues in the 3D reconstruction problems. In these problems, the main goal is to create a three-dimensional model from a sequence of 2D captured images during different times. That part of the scene which is rendered by a camera is often modeled by a frustum. Calculating the amount of intersection of two camera view frustums at different times can help to solve this problem. However, there are two major difficulties. First, calculating the intersection of two frustums, in general, is so complicated. And second, there are some uncertainties in the moving camera parameters over time. In this paper,... 

A bi-objective stochastic capacitated multi-facility location–allocation problem is presented where the customer demands have Bernoulli distributions. The capacity of a facility for accepting customers is limited so that if the number of allocated customers to the facility is more than its capacity, a shortage will occur. The problem is formulated as a bi-objective mathematical programming model. The first objective is to find optimal locations of facilities among potential locations and optimal allocations of stochastic customers to the facilities so that the total sum of fixed costs of establishment of the facilities and the expected values of servicing and shortage costs is minimized. The... 

In this paper, a restricted structure of PID controller is proposed for automobile gas turbine by considering a LQG cost function. So PID Controller coefficients are calculated by minimizing this cost function. One of the most important characteristics of this approach, its ability to design various structure PID controllers by solving optimization problem only for one time, moreover it can approximate main optimization problem by a repetitive Quadratic optimization Problem (QP). This approach is convex optimization and has an analytic solution; therefore its calculations are not complicated. In defined cost function, there are two weighting functions, control error and control action; they... 

In future wireless networks, network functions virtualization lays the foundations for establishing a new dynamic resource management framework to efficiently utilize network resources. In this paper, a network service can be viewed as a chain of virtual network functions (VNFs), called a service function chain (SFC), served via placement, admission control (AC), and embedding into network infrastructure, based on the resource management objectives and the state of network. To fully exploit such a potential and reach higher network performance, resource management stages should be jointly performed. To this end, two main challenges are: how to present a system model that formulates 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... 

Heterogeneous networks (HetNets) provide the demand for high data rates. In this study, we analyze the coexistence of femtocells and device-to-device (D2D) communication with macrocells. Interference management and decreasing energy consumption are two important issues in HetNets. To this end, we propose an efficient fractional frequency reuse (FFR)-based spectrum partitioning scheme to reduce the cross-tier interference. We also propose to use different optimization problems for resource allocation in different tiers. For this purpose, an energy efficient optimization problem is applied to D2D user equipment. Further, an optimization problem based on the spectral efficiency, i.e.,... 

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... 

Cloud manufacturing as an emerging service-oriented manufacturing paradigm integrates and manages geographically distributed manufacturing resources such that complex and highly customized manufacturing tasks can be performed cooperatively. The service composition and optimal selection (SCOS) problem, in which manufacturing cloud services are optimally selected for performing subtasks, is one of the key issues for implementing a cloud manufacturing system. In this paper, we propose a new mixed-integer programming model for solving the SCOS problem with sequential composition structure. Unlike the majority of previous research on the problem, in the proposed model, the transportation between... 

This paper presents a new method for restoration of distribution networks after a fault occurrence. This problem is solved from the viewpoint of the distribution system operator with the main goal of minimizing the operating cost during the fault clearance period. The effects of distributed generation (DG) units and direct load control (DLC) programs are considered in designing the proposed restoration procedure. Moreover, the uncertainties associated with the predicted loads of different nodes and the availability of DG are modeled here. Robust optimization is used to model the uncertainties of restoration problems and manage their associated risks. Finally, a robust reconfiguration plan is... 

This paper presents optimal scheduling in a two-machine flow shop, in which the objective function is to minimize the sum of maximum earliness and tardiness (n/2/P/ETmax). Since this problem tries to minimize earliness and tardiness, the results can be useful for different production systems such as just in time (JIT). This objective function has already been considered for n jobs and m machines, but the proposed algorithms are not efficient to solve large scale problems. In this paper, neighborhood conditions are developed and the dominant set for any optimal solution is determined. The branch-and-bound (B&B) method is used to solve the problem and the proper upper and lower bounds are also... 

A formulation of the Element Free Galerkin (EFG), one of the mesh-less methods, is developed for solving coupled problems and its validity for application to soil-water problems is examined through numerical analysis. The numerical approach is constructed to solve, two governing partial differential equations of equilibrium and the. continuity of pore water, simultaneously. Spatial variables in a weak form, the displacement increment and excess pore, water pressure increment, are discretized using the same EFG shape functions. An incremental constrained Galerkin weak form is used to create the discrete system equations and a fully implicit scheme is used to create the discretization of the... 

Nowadays, content distribution is of high attention in peer to peer information systems. There are two main problems that could be mentioned in this context. The first problem is how to disseminate fragments of information efficiently and the next is to avoid missing same rare fragments towards end of download. For overcoming these problems, a new mechanism is presented in this paper which uses gossip algorithms on basis of social networks. Our mechanism maintains simplicity of gossip and has low overhead. This mechanism includes two phases for managing traffic and solving bottleneck problem: one for spreading rumors inside the social network and finding network of interests and the other...