Sharif Digital Repository

Incorporating outsourcing in scheduling is addressed by several researchers recently. However, this scope is not investigated thoroughly, particularly in the job shop environment. In this paper, a new job shop scheduling problem is studied with the option of jobs outsourcing. The problem objective is to minimise a weighted sum of makespan and total outsourcing cost. With the aim of solving this problem optimally, two solution approaches of combinatorial optimisation problems, i.e. mathematical programming and constraint programming are examined. Furthermore, two problem relaxation approaches are developed to obtain strong lower bounds for some large scale problems for which the optimality is... 

As a promising solution for future indoor access networks, resource allocation in Visible light communication or LiFi networks is subject to lots of researches. An interesting approach for network algorithm design is to use some knowledge about the future of the network. With this regards, the anticipatory design may improve the performance of the system in terms of delay and throughput. This paper reviews the state-of-the-art anticipatory algorithms proposed in the literature, given different prediction capabilities. The key element that all of these algorithms share is to find an event that correlates the current actions to the performance of the network in the future. Apart from the... 

In this paper, exergy analysis of a steam power plant located in southern Iran named Zarand power plant has been studied. In order to optimize the performance of the Rankine cycle and achieve higher exergy efficiency, several parameters have been considered as decision variables. Knowing that there is the ability to change some of the parameters in the specific range in the process of electricity production in power plant, temperature and output pressure of the boiler and output pressure of four steps of extraction turbine have been selected as six decision variables. Also, exergy efficiency has been considered as the objective function. For this purpose, the exergy efficiency of the system... 

This paper develops a stochastic geometry-based approach for the modeling, analysis, and optimization of wireless cloud caching networks comprised of multiple-antenna radio units (RUs) inside clouds with coordinated multi-point transmissions and guard zones. We consider Poisson cluster processes to model RUs and users, and the probabilistic content placement to cache files in RUs. Accordingly, we study the exact hit probability for a user of interest for two strategies; closest selection, where the user is served by the closest RU that has its requested file, and best power selection, where the serving RU having the requested file provides the maximum instantaneous received power at the... 

We investigate various types of fuzzy linear programming problems based on models and solution methods. First, we review fuzzy linear programming problems with fuzzy decision variables and fuzzy linear programming problems with fuzzy parameters (fuzzy numbers in the definition of the objective function or constraints) along with the associated duality results. Then, we review the fully fuzzy linear programming problems with all variables and parameters being allowed to be fuzzy. Most methods used for solving such problems are based on ranking functions, α-cuts, using duality results or penalty functions. In these methods, authors deal with crisp formulations of the fuzzy problems. Recently,... 

The colorization of gray-scale images has always been a challenging task in computer vision. Recently, novel approaches have been introduced for unsupervised image translation between two domains using Generative Adversarial Networks (GANs). Since one can consider the gray-scale and colorful images as two separate domains, we propose a two-stage cycle-consistent network architecture to produce convincible images. First, an intermediate image is generated with a relatively uncomplicated objective function at the output. Next, at the second stage, the intermediate image is enhanced via a residual network structure with a more complicated objective function. Furthermore, by employing two... 

Energy-harvesting devices have been widely used to generate electrical power. Through the use of energy harvesting techniques, ambient vibration energy can be captured and converted into usable electricity in order to create self-powering systems. In the present study, to further improve the efficiency of energy-harvesting devices, a nonlinear piezomagnetoelastic energy harvester is proposed in two different configurations that is parallel and series. In order to optimize the generated electrical power, the physical parameters of the harvester are chosen as the design variables. Classical and Metaheuristic algorithms, namely, random search, genetic algorithm, and simulated annealing are... 

Grid scheduling problems are dynamic as the jobs and resources in the system vary overtime. The Rulebased scheduling algorithms are a new trend in grid scheduling which are applicable in dynamic grid environments; The arriving jobs waiting for execution is ordered according to a certain rule and they are dispatched for processing according to that order. Grid scheduling algorithms usually involve more than one objective function. In particular, it is not enough to minimize the Maximum completion time (Makespan) objective function without taking into consideration the lateness of the jobs (Tardiness). In this paper two novel dispatching rules are proposed that aims to minimize the maximum... 

Recently, several algorithms have been introduced for enhancing clustering quality by using supervision in the form of constraints. These algorithms typically utilize the pair wise constraints to either modify the clustering objective function or to learn the clustering distance measure. Very few of these algorithms show the ability of discovering clusters of different shapes along with satisfying the provided constraints. In this paper, a novel semi-supervised clustering algorithm is introduced that uses the side information and finds clusters of arbitrary shapes. This algorithm uses a two-stage clustering approach satisfying the pair wise constraints. In the first stage, the data points... 

This paper presents a method for the optimal allocation of Distributed generation in distribution systems. In this paper, our aim would be optimal distributed generation allocation for voltage profile improvement and loss reduction in distribution network. Genetic Algorithm (GA) was used as the solving tool, which referring two determined aim; the problem is defined and objective function is introduced. Considering to fitness values sensitivity in genetic algorithm process, there is needed to apply load flow for decision-making. Load flow algorithm is combined appropriately with GA, till access to acceptable results of this operation. We used MATPOWER package for load flow algorithm and... 

In this paper, we introduce a novel and robust approach to quantized matrix completion. First, we propose a rank minimization problem with constraints induced by quantization bounds. Next, we form an unconstrained optimization problem by regularizing the rank function with Huber loss. Huber loss is leveraged to control the violation from quantization bounds due to two properties: first, it is differentiable; and second, it is less sensitive to outliers than the quadratic loss. A smooth rank approximation is utilized to endorse lower rank on the genuine data matrix. Thus, an unconstrained optimization problem with differentiable objective function is obtained allowing us to advantage from... 

The problem of aerodynamic shape optimization of unguided projectiles has been investigated. Two stochastic optimization methods have been applied to solve the problem. These include a Genetic Algorithm (GA) and the recently developed Continuous Ant Colony System (CACS), which is based on the well-known Ant Colony Optimization meta-heuristic. The objective function is defined as the summation of normal force coefficients over a set of given flight conditions. An engineering code (EC) is used to calculate the normal force coefficients over the flight conditions. The obtained results of CACS+EC are compared with those of GA+EC, as well as the results of a previous work (GA +AeroDesign). The... 

We consider the problem of corrupted radar super-resolution, a generalization of compressed radar super-resolution in which one aims to recover the continuous-valued delay-Doppler pairs of moving objects from a collection of corrupted and noisy measurements. The received signal in this type consists of contributions from objects, outlier and noise. While this problem is ill-posed in general, tractable recovery is possible when both the number of objects and corrupted measurements are limited. In this brief, we propose an atomic norm optimization in order to find the delay-Doppler pairs and the outlier signal. The objective function of our optimization problem encourages both sparsity in the... 

Heaters are one of the central parts of natural gas reduction stations using turboexpanders to prevent the formation of hydrate and corrosion failure. This study intends to design a fired heater by applying a combustion sub-model to derive an optimal model for this kind of application. This model is developed to accurately consider all subsections of the fired heater namely radiation, convection, and shield sections, as well as flue gas composition, and its volume. Within this context, a multi-objective optimization is employed to identify the optimal design of the gas-fired heater in the natural gas reduction station for the Ramin power plant case study. The total economic and environmental... 

The concept of energy hub has been used recently to study multi-carrier energy systems. A model has been proposed in this paper for planning multi-hub energy system considering the competition between the hubs. The energy hubs are interconnected by a power grid. Hubs supply the demands for heat and electricity using various technologies and access to several energy carriers. To this aim, load zones were used to incorporate demand profiles for both heat and electricity in the different seasons of the year. Supplying the demand most cost-effectively is the objective function of each hub. These hubs select the optimum strategy separately in a competitive space. The power grid is owned by... 

This paper proposes a transient stability constrained controlled islanding (TSC-CI) approach against cascading events in power systems. Using the wide area measurements, the proposed islanding algorithm is implemented regarding the actual dynamic conditions of the resulted islands. Since the main concern, right after the execution of controlled network splitting, is the transient stability of synchronous machines, a transient energy function is utilized for proper network partitioning. The proposed transient stability criterion is expressed as a function of the transfer impedance between each pair of generators in the resulted islands. Transfer impedance between each pair of coherent... 

Energy consumption is a major challenge in IoT devices, which was aimed to be improved by employing energy-efficient objective functions (OFs) in the structure of the RPL routing protocol. Meanwhile, the majority of the existing OFs mainly perform the parent selection based on the gathered information from the routing layer. Nevertheless, based on our investigations, there exists a series of transmission operations in the medium access control (MAC) layer, which significantly affects the energy consumption in IoT devices. Therefore, in this article, we propose ELITE, an energy-efficient cross-layer OF, which introduces a novel routing metric, called strobe per packet ratio (SPR). SPR... 

The huge availability of data in the last decade has raised the opportunity for the better use of data in decision-making processes. The idea of using the existing data to achieve a more coherent reality solution has led to a branch of optimization called data-driven optimization. On the one hand, the presence of uncertain variables in these datasets makes it crucial to design robust optimization methods in this area. On the other hand, in many real-world problems, the closed-form of the objective function is not available and a meta-model based framework is necessary. Motivated by the above points, in this paper a Gaussian process is used in a Bayesian optimization framework to design a... 

An efficient isogeometric-based framework is presented to integrate optimum design and formability analysis of sheet metal forming processes. To assess the quality of the formed parts, several objective functions such as fracture, wrinkling, thickness variation, and stretching are studied. In this framework, geometric parameters of addendum surfaces and middle tools are considered as design variables, the objective functions are calculated using the recently developed one-step and multi-step inverse isogeometric methods, and the optimum design variables are obtained using the genetic global optimization algorithm. The major advantage of employing the inverse methods is to analyze the... 

The standardized IPv6 Routing Protocol for Low-power and Lossy Networks (RPL) has enabled efficient communications between thousands of smart devices, sensors, and actuators in a bi-directional, and end-to-end manner, allowing the connection of resource constraint devices in multi-hop IoT infrastructures. RPL is designed to cope with the major challenges of Low-power and Lossy Networks (LLNs), specifically their energy-efficiency. However, RPL is facing with severe congestion and load balancing problems, leading to a low Packet Delivery Ratio (PDR) in the network. For the first time since the declaration of RPL, in this paper we explain that ignoring the specifications of the reception and...