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Total 398 records

#### Disease diagnosis with a hybrid method SVR using NSGA-II

, Article Neurocomputing ; Vol. 136 , 2014 , pp. 14-29 ; Habibi, J ; Alizadehsani, R ; Sharif University of Technology
Abstract

Early diagnosis of any disease at a lower cost is preferable. Automatic medical diagnosis classification tools reduce financial burden on health care systems. In medical diagnosis, patterns consist of observable symptoms and the results of diagnostic tests, which have various associated costs and risks. In this paper, we have experimented and suggested an automated pattern classification method for classifying four diseases into two classes. In the literature on machine learning or data mining, regression and classification problems are typically viewed as two distinct problems differentiated by continuous or categorical dependent variables. There are endeavors to use regression methods to...

#### Online undersampled dynamic MRI reconstruction using mutual information

, Article 2014 21st Iranian Conference on Biomedical Engineering, ICBME 2014 ; 17 February , 2014 , Pages 241-245 ; ISBN: 9781479974177 ; Ghaffari, A ; Fatemizadeh, E ; Sharif University of Technology
Abstract

We propose an algorithm based on mutual information to address the problem of online reconstruction of dynamic MRI from partial k-space measurements. Most of previous compressed sensing (CS) based methods successfully leverage sparsity constraint for offline reconstruction of MR images, yet they are not used in online applications due to their complexities. In this paper, we formulate the reconstruction as a constraint optimization problem and try to maximize the mutual information between the current and the previous time frames. Conjugate gradient method is used to solve the optimization problem. Using Cartesian mask to undersample k-space measurements, the proposed method reduces...

#### Multi-job lot streaming to minimize the weighted completion time in a hybrid flow shop scheduling problem with work shift constraint

, Article International Journal of Advanced Manufacturing Technology ; Vol. 70, Issue. 1-4 , January , 2014 , pp. 501-514 ; ISSN: 02683768 ; Mahdavi, I ; Hassanzadeh, R ; Mahdavi-Amiri, N ; Mojarad, M ; Sharif University of Technology
Abstract

Lot streaming means breaking a lot into sublots, where sublots may be transferred to a number of machines for the operations. Here, the multi-job lot streaming problem in a multistage hybrid flow shop having identical parallel machines at stages with work-in-process (WIP) jobs, work shifts constraint, and sequence-dependent setup times is studied. The aim is to minimize the sum of weighted completion times of jobs in each shift in order to furnish a better machine utilization for the following shifts. Our model in meeting the job demands appropriates job scheduling onmachines for processing, the sequence of operations on allocated machines, the size of the sublots in the work shifts, the...

#### Outlier-aware dictionary learning for sparse representation

, Article IEEE International Workshop on Machine Learning for Signal Processing, MLSP ; 14 November , 2014 ; ISSN: 21610363 ; ISBN: 9781479936946 ; Sadeghi, M ; Joneidi, M ; Babaie Zadeh, M ; Jutten, C ; Sharif University of Technology
Abstract

Dictionary learning (DL) for sparse representation has been widely investigated during the last decade. A DL algorithm uses a training data set to learn a set of basis functions over which all training signals can be sparsely represented. In practice, training signals may contain a few outlier data, whose structures differ from those of the clean training set. The presence of these unpleasant data may heavily affect the learning performance of a DL algorithm. In this paper we propose a robust-to-outlier formulation of the DL problem. We then present an algorithm for solving the resulting problem. Experimental results on both synthetic data and image denoising demonstrate the promising...

#### Design of a robust model predictive controller with reduced computational complexity

, Article ISA Transactions ; Volume 53, Issue 6 , 1 November , 2014 , Pages 1754-1759 ; ISSN: 00190578 ; Haeri, M ; Sharif University of Technology
Abstract

The practicality of robust model predictive control of systems with model uncertainties depends on the time consumed for solving a defined optimization problem. This paper presents a method for the computational complexity reduction in a robust model predictive control. First a scaled state vector is defined such that the objective function contours in the defined optimization problem become vertical or horizontal ellipses or circles, and then the control input is determined at each sampling time as a state feedback that minimizes the infinite horizon objective function by solving some linear matrix inequalities. The simulation results show that the number of iterations to solve the problem...

#### Efficient upper and lower bounding methods for flowshop sequence-dependent group scheduling problems

, Article European Journal of Industrial Engineering ; Vol. 8, issue. 3 , 2014 , pp. 366-387 ; ISSN: 17515254 ; Salmasi, N ; Sharif University of Technology
Abstract

In this research, a permutation flowshop sequence-dependent group scheduling problem with minimisation of total completion time is considered. Since the problem is shown to be strongly NP-hard, a hybrid genetic (HG) algorithm is proposed. The only available lower bounding (LB) method for the proposed research problem in the literature based on branch and price (B&P) algorithm is also enhanced by proposing efficient method to solve sub-problems and proposing a better branching rule. A statistical comparison shows that both the proposed HG algorithm and the proposed LB have better performance than the other methods from the literature with an average 5.96% percentage gap. [Received 13 December...

#### A particle swarm optimization approach for robust unit commitment with significant vehicle to grid penetration

, Article Iranian Conference on Intelligent Systems, ICIS 2014 ; 2014 ; Aien, M ; Rashidinejad, M ; Fotuhi-Firouzabad, M
Abstract

Smartening of contemporaneous power delivery systems in conjunction with increased penetration of vehicle to grid (V2G) technology, changes the way market participants play their role in the market operation to maximize their profit. In V2G technology, plug-in electric vehicles (PEV) have bidirectional power flows i.e. they can either inject power to the grid or draw power from it. In recent years, the V2G technology has found a world wild attention due to its important advantages such as the peak load reduction and providing system reserve, to name a few. The unit commitment (UC) is a power system operation problem which is used to find the optimal operation schedule of generation units....

#### An approximation algorithm for computing the visibility region of a point on a terrain and visibility testing

, Article VISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications ; Vol. 3, issue , January , 2014 , p. 699-704 ; Ghodsi, M ; Gudukbay, U ; Golkari, M ; Sharif University of Technology
Abstract

Given a terrain and a query point p on or above it, we want to count the number of triangles of terrain that are visible from p. We present an approximation algorithm to solve this problem. We implement the algorithm and then we run it on the real data sets. The experimental results show that our approximation solution is very close to the real solution and compare to the other similar works, the running time of our algorithm is better than their algorithm. The analysis of time complexity of algorithm is also presented. Also, we consider visibility testing problem, where the goal is to test whether p and a given triangle of train are visible or not. We propose an algorithm for this problem...

#### A hybrid vendor managed inventory and redundancy allocation optimization problem in supply chain management: An NSGA-II with tuned parameters

, Article Computers and Operations Research ; Vol. 41, issue. 1 , 2014 , p. 53-64 ; Sadeghi, S ; Niaki, S. T. A ; Sharif University of Technology
Abstract

In this research, a bi-objective vendor managed inventory model in a supply chain with one vendor (producer) and several retailers is developed, in which determination of the optimal numbers of different machines that work in series to produce a single item is considered. While the demand rates of the retailers are deterministic and known, the constraints are the total budget, required storage space, vendor's total replenishment frequencies, and average inventory. In addition to production and holding costs of the vendor along with the ordering and holding costs of the retailers, the transportation cost of delivering the item to the retailers is also considered in the total chain cost. The...

#### Comparison between different multi-objective approaches to distribution network planning

, Article IET Conference Publications ; Volume 2013, Issue 615 CP , 2013 ; 9781849197328 (ISBN) ; Eini, B. J ; Mirvazand, M ; Safari, M ; Sharif University of Technology
2013

Abstract

Distribution companies try to meet different goals such as increasing profitability, reducing investment and improving reliability indices. Therefore, distribution network planning has converted into complex multi-objective optimization problems. Mathematicians and operation research experts have developed many methods which can be used for solving these problems. Despite all efforts to develop applicable approaches for these problems, there is still no general consensus on project selection policy. Evaluating the strengths and weaknesses of each network optimization strategy selection in pragmatic manner is the objective of current research. In this paper, many methods used in network...

#### Dictionary learning for sparse representation: A novel approach

, Article IEEE Signal Processing Letters ; Volume 20, Issue 12 , 2013 , Pages 1195-1198 ; 10709908 (ISSN) ; Babaie Zadeh, M ; Jutten, C ; Sharif University of Technology
2013

Abstract

A dictionary learning problem is a matrix factorization in which the goal is to factorize a training data matrix, Y, as the product of a dictionary, D, and a sparse coefficient matrix, X, as follows, Y ≈ DX. Current dictionary learning algorithms minimize the representation error subject to a constraint on D (usually having unit column-norms) and sparseness of X. The resulting problem is not convex with respect to the pair (D, X). In this letter, we derive a first order series expansion formula for the factorization, DX. The resulting objective function is jointly convex with respect to D and X. We simply solve the resulting problem using alternating minimization and apply some of the...

#### Multi-period lot sizing and job shop scheduling with compressible process times for multilevel product structures

, Article International Journal of Production Research ; Volume 51, Issue 20 , 2013 , Pages 6229-6246 ; 00207543 (ISSN) ; Seyedhoseini, S. M ; Modarres, M ; Heidari, M ; Sharif University of Technology
2013

Abstract

This paper presents mathematical modelling of joint lot sizing and scheduling problem in job shop environment under a set of working conditions. The main feature of the problem is to deal with flexible machines able to change their working speeds, known as process compressibility. Furthermore, produced items should be assembled together to make final products. In other words, the products have a multilevel structure, shown with bill of materials. As the problem is proved to be strongly NP-hard, it is solved by a memetic algorithm here. Computational experiences on the data of Mega Motor company are reported. Also, further experiences on random test data confirm the performance of the...

#### Makespan minimisation in flexible flowshop sequence-dependent group scheduling problem

, Article International Journal of Production Research ; Volume 51, Issue 20 , 2013 , Pages 6182-6193 ; 00207543 (ISSN) ; Salmasi, N ; Sharif University of Technology
2013

Abstract

In this research, the flexible flowshop sequence-dependent group scheduling problem with minimisation of makespan as the criterion (FFm|fmls, shgi|Cmax) is investigated. A mixed integer linear mathematical model for the research problem is developed. Since the research problem is shown to be NP-hard, a meta-heuristic algorithm based on memetic algorithm (MA) is developed to efficiently solve the problem. Also, a lower bounding technique based on the developed mathematical model is proposed to evaluate the quality of the proposed MA. The performance of the proposed MA is compared with the existing algorithm in the literature, i.e. tabu search (TS), by solving the available test problems in...

#### Discrete kinematic synthesis of discretely actuated hyper-redundant manipulators

, Article Robotica ; Volume 31, Issue 7 , 2013 , Pages 1073-1084 ; 02635747 (ISSN) ; Zohoor, H ; Korayem, M. H ; Sharif University of Technology
2013

Abstract

Discrete kinematic synthesis of discretely actuated hyper-redundant manipulators is a new practical problem in robotics. The problem concerns with determining the type of each manipulator module from among several specific types, so that the manipulator could reach several specified target frames with the lowest error. This paper suggests using a breadth-first search method and a workspace mean frame to solve this problem. To reduce errors, two heuristic ideas are proposed: two-by-two searching method and iteration. The effectiveness of the proposed method is verified through several numerical problems

#### Optimizing a multi-vendor multi-retailer vendor managed inventory problem: Two tuned meta-heuristic algorithms

, Article Knowledge Based Systems ; Volume 50 , September , 2013 , Pages 159-170 ; 09507051 (ISSN) ; Mousavi, S. M ; Niaki, S. T. A ; Sadeghi, S ; Sharif University of Technology
2013

Abstract

The vendor-managed inventory (VMI) is a common policy in supply chain management (SCM) to reduce bullwhip effects. Although different applications of VMI have been proposed in the literature, the multi-vendor multi-retailer single-warehouse (MV-MR-SW) case has not been investigated yet. This paper develops a constrained MV-MR-SW supply chain, in which both the space and the annual number of orders of the central warehouse are limited. The goal is to find the order quantities along with the number of shipments received by retailers and vendors such that the total inventory cost of the chain is minimized. Since the problem is formulated into an integer nonlinear programming model, the...

#### Beyond the cut-set bound: Uncertainty computations in network coding with correlated sources

, Article IEEE Transactions on Information Theory ; Volume 59, Issue 9 , 2013 , Pages 5708-5722 ; 00189448 (ISSN) ; Yang, S ; Jaggi, S ; Sharif University of Technology
2013

Abstract

Cut-set bounds are not, in general, tight for all classes of network communication problems. In this paper, we introduce a new technique for proving converses for the problem of transmission of correlated sources in networks, which results in bounds that are tighter than the corresponding cut-set bounds. We also define the concept of 'uncertainty region' which might be of independent interest. We provide a full characterization of this region for the case of two correlated random variables. The bounding technique works as follows: on one hand, we show that if the communication problem is solvable, the uncertainty of certain random variables in the network with respect to imaginary parties...

#### Joint single vendor-single buyer supply chain problem with stochastic demand and fuzzy lead-time

, Article Knowledge-Based Systems ; Volume 48 , 2013 , Pages 1-9 ; 09507051 (ISSN) ; Niaki, S. T .A ; Wee, H. M ; Sharif University of Technology
2013

Abstract

This study solves a chance-constraint supply chain problem with stochastic demand which follows a uniform distribution. Fuzzy delay times (moving, waiting and setup time) are assumed to be lot size dependent and shortage is partially backordered. The buyer is responsible for the costs incurred in ordering, holding, shortage and transportation, while the vendor is responsible for setup and holding costs. The service rate of each product has a chance constraint and the buyer has a budget constraint. Our objective is to determine the re-order point and the order quantity of the products such that the total cost is minimized. Since the problem is uncertain integer-nonlinear, two hybrid...

#### Composite power system adequacy assessment based on postoptimal analysis

, Article Turkish Journal of Electrical Engineering and Computer Sciences ; Volume 21, Issue 1 , 2013 , Pages 90-106 ; 13000632 (ISSN) ; Fotuhi Firuzabad, M ; Aminifar, F ; Sharif University of Technology
2013

Abstract

The modeling and evaluation of enormous numbers of contingencies are the most challenging impediments associated with composite power system adequacy assessment, particularly for large-scale power systems. Optimal power flow (OPF) solution, as a widely common approach, is normally employed to model and analyze each individual contingency as an independent problem. However, mathematical representations associated with diverse states are slightly different in one or a few generating units, line outages, or trivial load variations. This inherent attribute brings a promising idea to speed up the contingency evaluation procedure. In this paper, postoptimal analysis (POA), as a well-recognized...

#### Capacitated location allocation problem with stochastic location and fuzzy demand: A hybrid algorithm

, Article Applied Mathematical Modelling ; Volume 37, Issue 7 , 2013 , Pages 5109-5119 ; 0307904X (ISSN) ; Akhavan Niaki, S. T ; Sharif University of Technology
2013

Abstract

In this article, a capacitated location allocation problem is considered in which the demands and the locations of the customers are uncertain. The demands are assumed fuzzy, the locations follow a normal probability distribution, and the distances between the locations and the customers are taken Euclidean and squared Euclidean. The fuzzy expected cost programming, the fuzzy β-cost minimization model, and the credibility maximization model are three types of fuzzy programming that are developed to model the problem. Moreover, two closed-form Euclidean and squared Euclidean expressions are used to evaluate the expected distance between customers and facilities. In order to solve the problem...

#### Minimization of weighted earliness and tardiness for no-wait sequence-dependent setup times flowshop scheduling problem

, Article Computers and Industrial Engineering ; Volume 64, Issue 4 , April , 2013 , Pages 902-916 ; 03608352 (ISSN) ; Salmasi, N ; Sharif University of Technology
2013

Abstract

In this research, the no-wait flowshop sequence-dependent setup time scheduling problem with minimization of weighted earliness and tardiness penalties as the criterion, typically classified as Fm|nwt, S ijk|∑wj'Ej+wj ″Tj, is investigated. A mixed integer linear programming model for the research problem is proposed. As the problem is shown to be strongly NP-hard, several metaheuristic algorithms based on tabu search (TS) and particle swarm optimization (PSO) algorithms are developed to heuristically solve the problem. A timing algorithm is generated to find the optimal schedule and calculate the objective function value of a given sequence. In order to compare the performance of the...