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Learning disability (LD) is common problem in present world. Teachers and parents seek the newest instructional methods always. In this research, LD students in particular dyscalculia students are considered at elementary level. Assistive technology (AT) as assistive tools are designed and constructed to help LD students. One of tools of AT is software. The aim of this study is to introduce and design new mathematical software. Via quasi-experimental method, two basic addition and subtraction operations are taught through mathematical software with its special features for LD students at elementary level. Then findings are analyzed thereby ANOVA and sheffe tests. The results indicated that this technology has effect on the performance of these students and also, it is studied that the effect of using AT (Math Explorer software) on increasing ability of mathematical problem solving for dyscalculia students do not follow gender that is there is not significant difference between favorite performance of girl and boy LD students. Keywords: Learning Disabled Students, Dyscalculia Students, Assistive Technology, Math Explorer, Ability.

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Technique of Data Envelopment Analysis (DEA) involves methods conducted for desirable objective management of Decision Making Unit (DMU) that is same increasing of efficiency level. Data envelopment analysis furthermore determines the efficiency level, provides situation, removes inefficiency with evaluated benchmarking information. In this paper the use of the improvement Least-Distance measure with relation previous model by coplanar DMU, is proposed for computational dissipation at assess distance on these interior combinations, for determination the shortest projection from a considered unit to the strongly efficient production frontier. Therefore locate nearest path to improvement efficiency the evaluated DMU. Keywords: Data Envelopment Analysis, Least Distance, Coplanar DMU, Benchmarking.

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The performances of decision-making units (DMUs) can be evaluated from two different points of view optimistic and pessimistic and accordingly, two different efficiencies can be calculated for each DMU: the best relative efficiency and the worst relative efficiency. In the conventional methods of data envelopment analysis (DEA), only the best relative efficiency is evaluated. It is argued here that both efficiencies must be considered simultaneously, and any approach that considers only one of them will be biased. In this paper, it is proposed that to integrate both efficiencies in the form of an interval evaluates the overall performance of each DMU. To this end, a virtual DMU is used called the ideal DMU. The new DEA models with upper and lower bounds on efficiency are called the bounded DEA models. A numerical example is presented to illustrate the application of the proposed DEA models. Keywords: Data Envelopment Analysis (DEA), Optimistic and Pessimistic Efficiencies, Bounded DEA Models, Efficiency Interval.

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As can be seen from the definition of extended operations on fuzzy numbers, subtraction and division of fuzzy numbers are not the inverse operations to addition and multiplication . Hence, to solve the fuzzy equations or a fuzzy system of linear equations analytically, we must use methods without using inverse operators. In this paper, a novel method to find the solutions in which 0 is not the inner point of supports, of fully fuzzy linear systems (shown as FFLS ) is proposed, if they exist by an analytic approach. The system's parameters were splitted into two groups of nonpositive and nonnegative by solving a multi objective linear programming problem, MOLP , and employing an embedding method to transform n× n FFLS to 2n× 2n parametric form linear system and hence, transforming operations on fuzzy numbers to operations on functions. And finally, numerical examples are used to illustrate this approach. Keywords: Fuzzy Numbers, Fully Fuzzy Linear System, Systems of Fuzzy Linear Equations, Embedding Method, Splitting Method.

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The required storage space and the material handing cost in a warehouse hinge on the storage implementation decision. Effects of storage area reduction on order picking and storage space cost are incorporated. Moreover, merchandises which are in the same shape and can be stored beside each other easily or goods that don't cause any danger like causing a fire if be in touch with each other, can be stored in one class together. In this paper first a multi-objective class based storage model is presented in which two objectives are considered one is the sum of storage space cost and handing cost and the other is the quantitative objective "efficiency of storing products in one class". The demand rates and the second objective are evaluated with linguistic values. Fuzzy dynamic approach will be used to solve the proposed model considering an illustrative example to clarify it.

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This paper discusses that the fuzzy metagraphs can be used as a tool for scheduling and control of fuzzy projects. Often, available resources for executing projects may be limited. It is assumed the resources required to accomplish each activity of project (metagraph edges) is renewable. One of the common methods for scheduling projects is using the min-slack. So, first, the forward and backward computations for deterministic metagraphs are described. Then, assuming that the completion time of activities are positive trapezoidal fuzzy numbers, the forward and backward computations are generalized for fuzzy metagraphs. Consequently, completion time of project, earliest and latest time of start and end of activities and floating time of them are obtained as fuzzy numbers. Also, critical activities and critical paths are defined. Then, for scheduling, by using the selected ranking method, the activities of project (metagraph edges) based on min-slack ascending were ordered. Through some numerical examples, calculation steps and the results are illustrated.

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The purpose of this study is to utilize a new method for ranking extreme efficient decision making units (DMUs) based upon the omission of these efficient DMUs from reference set of inefficient and non-extreme efficient DMUs in data envelopment analysis (DEA) models with constant and variable returns to scale. In this method, an L2- norm is used and it is believed that it doesn't have any existing problems of such methods. Finally, two numerical examples for illustration and comparing the proposed method with other ranking approaches are presented. Keywords: Data Envelopment Analysis (DEA), Ranking, Efficiency.

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Efficiency measurement is critical for industries where firms do not face strong competition, as we cannot rely on the market to discipline the firms' efficiency. Railway is a typical example. At the same time the fact that railway produces multiple outputs using the common set of inputs calls for a delicate and sophisticated treatment in measuring the efficiencies. In this article, the DEA method is used to determine RAI (RahAhan Iran) efficiency comparison with other countries. The scale efficiency rate of RAI was calculated and showed the percentage of 0.564. Finally, by analyzing this performance, a suitability in inputs and outputs for reaching the efficiency boundary was resulted.

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Today, quality improvement and cost reduction are key factors for achieving business success, growth and position. One of the primary tools for quality improvement and cost reduction in online activities of statistical process control is control charts. As the need for monitoring several correlated quality characteristics is extensively growing, the use of multivariate control charts becomes more popular. Among these, the control chart is the most popular due to many advantages. In this paper, the variable sampling scheme is studied to increase the power of the fixed sampling rate ( ) control chart to show small shifts. In this study, one of the parameters of control chart, e.g., the sample size, vary between three values, depending on the most recent value. The design of control chart with three variable sample sizes ( 3 ) from the statistical and economic perspective has been investigated, when the shift in the process mean does not occur at the beginning but at some random time in the future. Therefore, the Markov Chain approach used to develop the cost function. Then, the genetic algorithm ( GA ) is applied to search for the optimal values of the parameters of the 3 control chart. Finally, numerical comparisons among and 3 schemes are made and discussed. Keywords: Multivariate T 2 Control Chart with Three Variable Sample Sizes (3VSS), Small Shifts, Markov Chain, Genetic Algorithm.

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In this paper, there are two competitors in a planar market. The first competitor, called, the leader, opens new facilities. After that, the second competitor, the follower, reacts to the leader’s action and opens r new facilities. The leader and the follower have got some facilities in advance in this market. The optimal locations for leader and follower are chosen among predefined candidate locations. In this paper, it is assumed that the demand is inelastic. Considering the huff model, customers share their demand among all facilities, probabilistically. The leader’s objective function is the maximization of its market share after the follower’s new facilities entry. The leader and follower problems are solved via an exact solution method. Keywords: Competitive Location, Leader-Follower, Huff-Type, Market Share.

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Flow shop scheduling problem with missing operations is studied in this paper. Missing operations assumption refers to the fact that at least one job does not visit one machine in the production process. A mixed-binary integer programming model has been presented for this problem to minimize the makespan. The genetic algorithm (GA) and tabu search (TS) are used to deal with the optimization problem. According to computational experiments on data sets, it is suggested that GA is a more appropriate method to solve this problem. GA can reach good-quality solutions in short computational time, and can be used to solve large scale problems effectively. Keywords: Flow Shop Scheduling, Missing Operation, Mixed-Binary Integer Programming, Genetic Algorithm, Tabu Search.

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Risk management is one of the most prominent concepts which has recently been brought into sharp focus regarding security issues in computer networks. Scientifically speaking, risk in the field of network security is a generalized matter leading the organization to the provision of resolutions which target resources and profits of the organization. This paper has discussed what methods are to be adopted with respect to identification and classification of risk assessment and evaluation of computer networks using data mining. The proposed method uses support vector machine to generate and analyze results of risk evaluation. Considering available resources in the organization, the tasks performed by means of this method are of high accuracy therefore, results are hereby in accordance with theories of management and security and based on resources and organizational profits depending on adjustable parameters as inputs. Outcomes of this study can be implemented in a dynamically real-time defensive system. Keywords: Risk Management, Risk Evaluation Model, Network Vulnerability, Data Mining, Support Vector machine.

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Abstract as a single objective one. Measures like support, confidence and other interestingness criteria which are used for evaluating a rule, can be thought of as different objectives of association rule mining problem. Support count is the number of records, which satisfies all the conditions that exist in the rule. This objective represents the accuracy of the rules extracted from the database. Confidence represents the proportion of records for which the prediction of the rule (or model in the case of a complete classification) is correct, and it is one of the most widely quoted measures of quality, especially in the context of complete classification. Interestingness measures how much interesting the rule is. Using these three measures as the objectives of rule mining problem, this article uses a Simulated Annealing algorithm to extract some useful and interesting rules from any Market-basket type databases. The experimental results show that the algorithm may be suitable for large and noisy datasets but don’t stay in local minimum. Keywords: Simulated Annealing, Numeric Association Rule Mining.

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Blind students have limitations that their teachers have to apply efficient educational methods for them. Since mathematics concepts are abstract for blind students and they cannot understand these concepts deeply, this research has tried that used and introduced cooperative learning method for this reason. Blind students have high listening capacity then cooperative learning method can promote other their capacities. Through quasi-experimental method, 40 girl blind students are chosen at third grade of elementary level. Basic mathematical operations are taught via cited method. The results of T-tests indicated that cooperative learning can be positive effect on solving capacity of blind students for basic mathematical concepts. Keywords: Blind, Mathematical Concepts, Cooperative Learning Method, Teaching.

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This paper proposes a new mathematical model for multi-objective redundancy allocation problem (RAP) without component mixing in each subsystem when the redundancy strategy can be chosen for individual subsystems. Majority of the mathematical model for the multi-objective redundancy allocation problems (MORAP) assume that the redundancy strategy for each subsystem is predetermined and fixed. In general, active redundancy has received more attention in the past. However, in practice both active and cold-standby redundancies may be used within a particular system design and the choice of the redundancy strategy becomes an additional decision variable. The proposed model for MORAP simultaneously maximizes the reliability and the net profit of the system. And finally, to clarify the proposed mathematical model a numerical example will be solved. Keywords: Redundancy Allocation Problem, Serial-Parallel System, Redundancy Strategies, MORAP.

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In data envelopment analysis, anyone can do classification decision units with efficiency scores. It will be interesting if a method for classification of DMUs without regarding to efficiency score is obtained. So in this paper, the classification of Decision Making Units (DMUs) is done according to the additive model without being solved for obtaining scores efficiency. This is because it is known that the additive model is the simplest non-radial model in DEA. In fact, the classification of DMUs to a set of efficient, weak efficient, and inefficient units, based upon feasibility concept is done here. Especially, the models and theorems for this aim are presented. Keywords: Data Envelopment Analysis, Classification, Decision Making Units.

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In today’s economy, manufacturing plants must be able to operate efficiently and respond quickly to changes in the product mix and demand.[1] Layout design has a significant impact on manufacturing efficiency. Initially, it was treated as a static decision but due to improvements in technology, it is possible to rearrange the manufacturing facilities in different scenarios. The Plant layout affects on the total cost in the industry. Nowadays Dynamic layout is becoming an important issue. Dynamic layout is the different layout at different time periods to satisfy the needs of industry due to change in product, or reduced product life cycle, or change in demand. Layout problem is a quadratic assignment problem, and for larger size problems it becomes impossible to be solved. So, for solving this problem Meta heuristic algorithms are used. In this paper, Dynamic layout problem is solved using Genetic algorithm. This Dynamic Problem is restricted up to two-time periods only. Keywords: Dynamic Layout, Heuristics, Genetic Algorithm.

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This paper presents a novel multi-objective mathematical model of a periodic vehicle routing problem (PVRP) in a competitive situation for obtaining more sales. In such a situation, the reaching time to customers affects the sale amount therefore, distributors intend to service customers earlier than other rivals for obtaining the maximum sale. Moreover, a partial driver’s benefit is related to the amount of their sale thus, the balance of goods based on the vehicles capacity is important. Due to its complexity, it is so difficult to optimally solve this problem in a reasonable computational time. Hence, two algorithms are proposed based on multi-objective particle swarm optimization (MOPSO) and NSGAII algorithm. A comparison of our results with three performance metrics confirms that the proposed MOPSO is an efficient algorithm for solving the competitive PVRP with a reasonable computational time. Keywords: Periodic Vehicle Routing Problem, Competitive Time Windows, Multi Objective Optimization, MOPSO.

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Data envelopment analysis (DEA) is a method for recognizing the efficient frontier of decision making units (DMUs).This paper presents a Context-dependent DEA which uses the interval inputs and outputs. Context-dependent approach with interval inputs and outputs can consider a set of DMUs against the special context. Each context shows an efficient frontier including DMUs in particular levels. The Context-dependent DEA with interval inputs and outputs can measure (i) the attractiveness when DMUs showing weaker performance are selected as an appraisal context, and (ii) the interval progress when DMUs showing better performance are selected as the appraisal context. Keywords: Interval Inputs and Outputs, Context-Dependent Data Envelopment Analysis, Attractiveness, Progress, Value Judgment.

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Traditional DEA models ignore the internal process of production systems and are not able to identify the cause of deficiency in efficiencies measuring. At this research, traditional DEA model and two-stage DEA model were used to measure the efficiency of Iranian private insurance companies during 2007-2009. The results indicated that the traditional DEA model is not suitable for such kind of network systems. In marketing perspective, Melat and Hafez companies were efficient during the study period. But these two companies are not efficient due to weakness in investment sub-process. Wilcoxon’s signed-rank test was used to identify the main reason of weakness between efficiency average of marketing sub-process and investment sub-process with significant level of 0.01. The results indicated that the investment weakness is the main reason of insurance companies’ deficiencies during the studied period. Keywords: Two-Stage DEA, Insurance Industry, Marketing Sub-Process, Investment Sub-Process.