Ranking industry normally helps find hot sectors and attract potential investors to invest in appropriate plans. Ranking various industries is also a multiple criteria decision making problem. In this paper, we present an empirical investigation to rank different industries using the art of data envelopment analysis (DEA). The inputs of our proposed DEA model include capital, employment and importance coefficient and outputs are exports, ecological effects and added value. In addition, exports, value added and environmental investment are used as outputs of DEA method. Since the results of DEA may consider more than one efficient unit, so we implement Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique to rank efficient units. In our case study, there were 15 different sectors from various industries and the implementation of DEA technique recommends 8 efficient units. The implementation of TOPSIS among these efficient units has suggested that Chemical industry could be considered as the most attracting industry for investment.

Contractor selection plays essential role on development of business industries and any selection strategy is normally involved with various factors. This paper presents an empirical investigation to determine important factors influencing contractor selection to increase profitability. The proposed model of this paper is implemented for an Iranian constructor firm named Kayson Company located in city of Tehran, Iran. The study has been accomplished among top managers who worked for this firm. Using structural equation modeling, the study determines that five factors including performance, believes, flexibility, quality, price and services influence on profitability when a contractor is to be chosen.

There are many opportunities and challenges in the area of Indian technical education due to liberalization and globalization of economy. One of these challenges is how to assess the performance of technical institutions based on multiple criteria. The purpose of this paper is to describe and illustrate an application of a structured approach to determine relative performance and ranking of seven Indian Institutes of Technology (IITs) under multi-criteria environment. To evaluate the alternatives in respect to stakeholders’ preference we suggest a new methodology consisting of fuzzy AHP, DEA and TOPSIS. Fuzzy AHP technique is used to determine the weights of criteria and some linguistic terms are applied to assess performance under each criterion, then in order to determine the value of linguistic terms we use the data envelopment analysis (DEA) method. Finally TOPSIS method is used to aggregate performance scores under different criteria into an overall performance score for each institution and ranking the institution according to their overall performance score. The proposed fuzzy AHP–DEA–TOPSIS methodology is applicable to any multiple criteria decision making (MCDM) problem due to its generic nature.

Considering the importance and extensive range of decision-making, scientists from various fields have had many discussions on this issue. Various models have been proposed to facilitate decision-making and have had much utilization. In many site selection problems, multiple objectives must be obtained, simultaneously. This study uses a mathematical model to select a suitable location for the refinery in the multi attribute environment. The proposed model uses a large amount of qualitative and quantitative information in the frame of multi objective functions for the first time in the refinery site selection and is flexible enough to use decision makers’ opinions in order to achieve goals. For this reason, after a brief overview of the selected area characteristics, using analytic hierarchy process (AHP) for weighting the criteria, a mathematical operation research model is proposed to determine the best alternatives.

In this paper, we have provided hands-on experience in systematic design, implementation and flight test of an atmospheric data acquisition flying vehicle as a standard CanSat telemetry mission. This system is designed for launching from a rocket at a separation altitude about 1000-meter. During its flight, the reusable flying vehicle collects environmental data and transmits it directly to the ground station. The ground station, which is implemented at a pre-defined radio frequency band receives data and plots the respective graphs. The design performs based on a systematic approach, in which the first step is set aside to mission and objectives definition. In the next step, the system requirements are identified and the required main subsystems and elements with their technical requirements will be extracted. The structure analyses were also performed by ABAQUS software to obtain the natural frequency and the mode shape. The wireless communications, onboard microcontroller programming, sensor interfacing and analog to digital conversion describe the basic technologies employed in the system implementation. This flying vehicle in comparison with the other similar ones is more lightweight, has few interface circuits and high precision sensors. According to the flight test outputs, low power consumption, high transmit line up to 2Km despite of limitation in TX power and up to 10g normal acceleration withstanding are important specific characteristics of the implemented flying system.

This paper presents a study to investigate the effects of open innovation factors on supply chain behavior in Iranian gas industry. The study uses two questionnaires, one to measure the effects of open innovation factors developed by Chesbrough (2003) [Chesbrough, H. W. (2003). Open innovation: The new imperative for creating and profiting from technology. Harvard Business Press.] and the other to measure the effects of supply chain behavior. Using Pearson correlation ratio as well as Stepwise regression model, the study has determined a positive and meaningful relationship between open innovation and supply chain behavior. In our survey, while intellectual property management and networking had no impact on supply chain behavior, three variables of research and development, cooperation and entrepreneurship influence positively on supply chain behavior.

Nowadays, the advance and enhance in competitive area, convert the supply chain management into one of the most important issues for industries, organization, and firms. Increasing the quality of products, decreasing the costs, and representing the satisfying service are the primary objectives of organization and managers. Apart from that, the amount of CNGs (such as CO2) has been raised by industrial activities. Therefore, the concern of air pollution motivates managers and researchers to consider this issue in the process. This paper represents a multi objective supply chain network fuzzy programming, which is multi product, multi period, multi-layer, and has reverse product network. Operational risks are considered as deficiency in suppliers’ units and production center. The model’s duty is to choose the optimal suppliers based on different factors such as selling price, the average of deficiency and transportation costs. In order to solve the model, the Jimenez and TH approach are used and for large-scale problems, the paper uses the NSGA-II algorithm.

During the past five decades, there have been tremendous efforts to offer different methods for portfolio management. The primary objective of many of these methods is to provide a trade-off between risk and reward. The proposed study of this paper uses analytical hierarchy process (AHP) and grey relational analysis to offer a method for portfolio management. The proposed method of this paper uses a statistical sample consists of 16 firms whose shares were trading during the fiscal year of 2010 on Tehran Stock Exchange. The study uses AHP and gray relational analysis to assign weight to each firm. We also use a linear programming technique to model the resulted problem by considering some realistic constraints.

The effect of first nonsingular stress term of elastic stress field on fracture toughness around bi-material notch tip is studies in this paper. First, a modified maximum tangential stress criterion (MMTS) is proposed for determination of the fracture toughness at the tip of the interface notches. The proposed criterion takes into account the effect of first nonsingular stress term as well as the singular stress terms. Then, the effect of I-stress on determination of the fracture toughness is studied analytically. Finally, the proposed criterion is applied on a finite element (FE) simulated laboratory specimen. A very good correlation was observed between the FE results and theoretical predictions.

Ranking various alternatives has been under investigation and there are literally various methods and techniques for making a decision based on various criteria. One of the primary concerns on ranking methodologies such as analytical hierarchy process (AHP) is that decision makers cannot express his/her feeling in crisp form. Therefore, we need to use linguistic terms to receive the relative weights for comparing various alternatives. In this paper, we discuss ranking different alternatives based on the implementation of preference relation matrix based on intuitionistic fuzzy sets.