Accidents and unpredictable diseases in different parts of the world, especially in big cities influence many lives. Most of the accidents and/or sudden diseases require quick aid due to its relation to people’s life, and the least time might affect the result of the aid significantly. It is noteworthy that finding the appropriate solution is under influence of considering the financial and treatment limitations. Integration of decision making in relief logistics leads to establish a better condition. Also, with regards to the unpredictability of relief demand, uncertain conditions should be investigated in a more appropriate way of planning process. This paper investigates a comprehensive and multi-level emergency Location allocation routing emergency problem under uncertain conditions with stable response to the different situations. In the presented model, the demand is defined by the emergency stations in order to represent the actual situations in real world. On the other hand, by the increase in the rate of providing services by the ambulances, the length of the queue will decrease and the costs will reduce due to the increase in the efficiency of the ambulances. A simulated annealing (SA) algorithm is developed to solve the problem. The obtained results show that the proposed algorithm has good performance. Finally, a sensitivity analysis is done to consider the effect of different values and uncertainty taken by parameters in real world.

This paper presents an empirical investigation on the effect of product market competition on transactions with related parties and company performance. The study selects a sample of 250 randomly selected firms whose common shares were traded on Tehran Stock Exchange. The study uses Herfindahl-Hirschman Index (HHI) to measure the market concentration and uses historical information over the period 2008-2012 to examine the hypotheses of the survey. Using simple regression analysis, the study has detected a positive relationship between HHI and related party transactions. In addition, the study has detected a negative relationship between competition and company performance measured by return on assets.

Tourism plays essential role in today’s economy and Iran has good position of tourism sources such as natural, historical, cultural, etc., although, these sources have not been utilized, properly. One of regions which have many potentiality and capabilities for developing Tourism in natural aspect is district and city of Galugah. The purpose of this study is to provide strategic assessment and optimization strategies for development of tourism industry to reach sustainable tourism development in this city. The study uses three techniques namely; Quantitative Strategic Planning Matrix (QSPM) and strengths, weaknesses, opportunities and threats (SWOT) to determine necessary guidelines for development of tourism in the city of Galugah, Iran. The study first uses SWOT to categorize different factors and then QSPM is applied to prioritize various factors. The results of this study show that presenting methods in initial process and analyzing assessment matrix of T2 external and internal factors i.e. pollution of environment and river and extinction of plants species by result of pollution and O2 i.e. suitable climate for developing natural Tourism efforts in summer have been recognized as most priority factors among external factors. Intense cold of region in summer (W3) and existence of unique amusement places (S5) such as Amarg were recognized as effective and most priority factors among internal factors on Tourism development of Galugah city.

Enterprise architecture procedure contains some instructions for conversion of enterprise architecture from the current state to the desirable state. This procedure generally contains 3 phases each of which is the basis and prerequisite of the next phase. These phases are: Strategic information technology planning, enterprise architecture planning and enterprise architecture execution. As each phase is a prerequisite of the next one, any fault in each phase causes bigger faults in final results. Therefore, each phase should be double checked to make sure no fault has occurred. The second phase can greatly influence the final results. Therefore the preparation of an executable enterprise architecture model and checking it with functional and non-functional requirements can prevent many faults and lead to execution of a perfect model of the enterprise. The primary objective of this research is to check the accuracy of EA behavior in achieving an appropriate architecture. In this research, official models have been used to propose a solution to transform the products of C4ISR framework to executable Petri nets. Finally, a method is proposed to check the accuracy of the mentioned model. The proposed solution makes the EA semi-automatically check the correctness of the enterprise architecture behavior and increase its accuracy.

The purpose of this paper is to discuss the state of the art on models and methods for reliability optimization problems (ROPs) including reliability allocation, redundancy allocation and reliability-redundancy allocation. There are literally few surveys for reviewing the literature of the ROPs. Tillman et al. (1980) classified the related papers by system structure, problem type, and solution methods, separately. In another work, Tzafestas (1980) reviewed system reliability optimization models and the optimization techniques. Yearout (1986) reviewed the literature related to standby redundancy. Kuo (2000) studied the system reliability optimization based on system structure and solution methods. Kuo and Prasad (2004) overviewed system reliability optimization methods. Later, Kuo (2007) reviewed recent advances in optimal reliability allocation problems. The present study adds to the previous literature surveys and focuses mainly on papers after year 2000 but with a quick review on the previous works so that the readers become familiar with the existing approaches. This research investigates the literature from system structure, system performance, uncertainty state and solution approach standpoints, simultaneously.

The present study endeavors to show an application of the multi objective optimization on the basis of ratio analysis (MOORA) method and technique for order performance by similarity to ideal solution (TOPSIS) method to select optimal process parameters in sheet hydroforming process. The right choice of the process parameters is critical to produce a final part with proper quality. In order to meet this characteristic, the important properties are the cup final thickness (FT), required forming force (FF) and radial stress (RS) at cup wall region. Nine alternatives for selecting the process parameters were taken into consideration based on Taguchi L9 orthogonal array. The limit drawing ratio (LDR), maximum pressure and prebulge pressure were selected as input variables. To solve the problem of process parameters’ selection, the two mentioned methods were used. A compromised weighting approach composed of Entropy and analytic hierarchy process (AHP) methods were used to weight all criteria. The alternatives ranking were performed using MOORA and TOPSIS methods and then the results were compared. The results achieved in both of the assessment represent that the alternative number 3, leads to the best multi performance features of the process among the 9 experiments. In this experiment LDR is 1.81, maximum pressure and prebulge pressure are 37 MPa and 15 MPa, respectively.

This paper introduces a new comprehensive four-parameter distribution called the modified generalized linear failure rate (MGLFR) distribution. The method generalizes some well-known and most commonly used distributions in reliability such as exponential, Rayleigh, linear failure rate, generalized linear failure rate and modified Weibull distribution. The study also investigates some essential properties of this new distribution and considers the problem of the evaluation of system reliability by describing the lifetimes of components based on a fuzzy MGLFR distribution and by developing fuzzy reliability characteristics. The results can be applied to determine the reliability of real objects where parameters of lifetime variable are subject to uncertainty.

As construction projects are becoming more deployed and more complicated at the same time, having an instrument for anticipation of success has become a primary requirement for every stakeholder. On this basis, several models have been introduced which implement different methods for anticipation of the entire goals or a series of goals of projects. In this research, at the first step, 16 criteria as instruments of anticipation of success and 33 factors as required instruments for obtaining success were extracted through library studies, semi-structured interviews and the Delphi method. At the next step, by having 169 questionnaires filled by senior managers of construction projects, the importance and priority of each of these 16 criteria and 33 factors for the initial phases of projects were determined according to Iran’s local conditions. Ultimately, through modeling of data by a propagation neural network including 35 hidden layers, the anticipator model for success of construction projects during their initial phases was developed with Performance and Regression. This model is able to anticipate the level of realization of projects’ success criteria according to the level of realization of success factors at the initial phase.

Supply chain members cannot act independently and they need to act as a part of a unified system and coordinated with other members. Therefore, a coordination mechanism may be necessary to motivate members to achieve coordination. In this paper, the coordination problem is studied in a two-level supply chain consisting of a supplier and a retailer where demand is a function of price and advertising expenditures in two scenarios. The first scenario is “No coordination”, and the other scenario is “coordination with Revenue sharing contract”. The models are solved using game theory, Cooperative and Nash equilibrium. Finally, numerical examples are presented indicating that the average expected profit in the second scenario, coordination with revenue sharing, is higher than the first scenario. In addition numerical examples indicate that as price and advertising elasticity to demand increase, profitability of supply chain decreases.

Cellular manufacturing is considered as a lean technique of producing similar parts using sells or groups of team members, workstations, or equipment to facilitate operations by removing setup and unnecessary cost components among various operations. Cell formation and layout planning are the most components of the cellular manufacturing. This paper presents a dynamic method to minimize different costs including the total cost of movements within and between cells and exceptional parts. In this study, the Hierarchical Genetic Algorithm (HGA) is used for solving the resulted model and the results are compared with genetic algorithm. The results have indicated that the proposed method could reach optimal solutions for some small and medium sized problems in reasonable amount of time.