This paper is concerned with the vibration and stability analysis of thick rectangular plates resting on elastic foundation, which is distributed over the particular area of the plate. A two-parameter (Pasternak) model is considered to describe the elastic foundation. The eigenvalue problem in 3-D domain is numerically solved by a combination of the finite element and differential quadrature method (DQM). The energy principle is employed to derive the governing equations in the framework of three-dimensional, linear and small strain theory of elasticity. The in-plane domain of the problem is discretized using two-dimensional finite elements and spatial derivatives of equations in the thickness direction are discretized in strong-form using DQM. As a first endeavor, the mixed FE-DQ method has been employed for 3-D buckling and free vibration analysis of rectangular thick plates partially supported by an elastic foundation. The accuracy of obtained results is validated by comparing to the few analytical solutions in the literature.

The Project Portfolio Selection is a complex process that involves many factors and considerations since the project is proposed until the project portfolio is finally selected. Project Portfolio Management is the iterative process of assessment, selection and implementation of projects, and the most important part of that is to select projects for portfolio where the or-ganization is required to identify and prioritize projects with the most objective alignment to its objectives. Since the selection of a suitable projects is very important, it is necessary to develop mathematical models to lead the organization towards the final goal. To achieve this goal, these models should reflect the organization's position, goals and priorities as much as possible. In this paper, we propose a multi - objective model for selecting the project portfolio that maximizes efficiency, quality while minimizes the risk involved in project execution.

Humanitarian assistance by foreign organizations in general and foreign military forces in particular, is typically provided in a non-neutral political environment. Local politics that range from national pride, through strained relations with the country offering military logistic support, to blatant aversion to the population in need, affect the ability to provide effective humanitarian aid. The current paper presents the use of mathematical modeling and robustness approach when the government of the affected area declines offers of aid from international organizations because of political constraints. The multi-objective model seeks to minimize unsatisfied demands and total costs of the government and suppliers. To explore the effects of various parameters and show managerial insights that can guide DMs under a variety of conditions, the sensitivity analysis of the experiments are presented.

In the past, due to the use of two-dimensional design, the probability of error in large projects increased. Over time, the need for a digital 3D model has increased in the lifetime of refineries, petrochemicals and power plants. Today, the editable digital 3D model is the basic needs of industrial plants. The Abadan Oil Refinery Co., due to its need for inspections and possible changes in the refinery, has also needed an editable 3D Digital Plant during the past few years. In this paper, with the development of a new methodology, the non-editable Navisworks® model of phase 1 and 3 of Abadan Oil Refinery was transformed into an editable Digital 3D model in AVEVA PDMS. In this methodology, the PDMS programming language called Programming Macro Language (PML) as well as .net code was used. Finally, using the Navisworks® model, these two phases, which consisted of 38 Areas, 2185 equipment, 17966 pipes, 7046 instruments, and 2617 structures were converted into an editable PDMS model for nine months.

During the past few years, there have been an increasing competition among auto producers. Customers have experienced emissions misrepresentation activities from well-known auto producers such as Volkswagen and Mitsubishi, and have increased their expectations, accordingly. This paper designs a questionnaire to measure factors influencing on customer satisfaction in Likert scale, and distributes it among 210 randomly selected people who purchased a product from an Iranian Auto maker named SAIPA. The questionnaire was validated by some experts and it was also verified using Cronbach alpha (α = 0.83). Using structural equation modeling with Varimax rotation, the study has detected four groups of factors including car specifications and options, before sales services, after sales services and payment policy, which influence the most on customer satisfaction.

There have been many unexpected natural disasters such as earthquake, flood, etc. in developing countries, which have created catastrophic incidents and we need to do appropriate planning for relief to reduce the possible casualties. Such actions normally face different challenges such as damages on transportation infrastructures including roads, bridges, etc. One of the primary actions for such crises management is associated with facility location for relief distribution centers. This paper presents a multi-objective mathematical problem and applies it for a real-world case study in northern region of Iran. The study uses Lp metric to handle different objectives and fuzzy programming is used to cope with uncertainty. The preliminary results indicate that the proposed study of this paper has been able to provide efficient results.

This paper presents a mathematical model to choose appropriate technology for production and capacity planning. The proposed study considers manufacturing planning in textile industry as a make-to-order (MTO) system by managing employees and water consumption and the possibility of outsourcing. The resulted model has been formulated as a mixed integer programming problem, which can be solved using a commercial software package. The implementation of the proposed study has been considered for a real-world case study and the results are discussed.

This paper formulates a multi-level supply chain network with a single producer, multi distributors and multi retailers during a finite planning horizon. The demand rate is assumed to be exponential function of time; shortages are allowed and completely backlogged. The stock is assumed to undergo deterioration as soon as it is produced. The production rate is dependent on demand rate and greater than the demand rate. Optimal solution for the proposed model is derived and using a numerical example, the behavior of the model is analyzed.

This paper models the process of ordered product design decision making. The problem is formulated by introducing the notion of Quality Loss to quantify the loss of design freedom incurred by the decision makers in the later stages of a cross-functional decision process. In this context, the optimal order is the decision order with the lowest quality loss, whose characterization is one of the contributions of this paper. In this paper, we present a novel decision support system for order in a Make-to-Stock or Make-to-Order production environment. The proposed decision support system is comprised of six steps. The customers are prioritized based on a new method. In this paper, the idea of the algorithm “Knapsack” is used to prioritize customers. Finally, numerical experiments are conducted to show the tractability of the applied mathematical programming model.

Data envelopment analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs). Traditional DEA models deal with measurements of relative efficiency of DMUs regarding multiple-inputs vs. multiple-outputs. One of the drawbacks of these models is the neglect of intermediate products or linking activities. Recently, DEA has been extended to examine the efficiency of network structures, where there are lots of sub-processes that are linked with intermediate parameters. These intermediate parameters can be considered as the outputs of the first stage and simultaneously as the inputs for the second stage. In contrast to the traditional DEA analysis, network DEA analysis aims to measure different sub-processes’ efficiencies in addition to the total efficiency. Lots of network DEA technique has been used recently, but none of them uses Analytic Hierarchy Process (AHP) in network DEA for assessing a network’s efficiency. In this paper, AHP methodology is used for considering the importance of each sub-process and network DEA is used for measuring total and partial efficiencies based on the importance of each department measured from AHP methodology. In this regard, the case of Iranian Handmade Carpet Industry (IHCI) is used.