Jafar Razmi; Hassan Haleh; Sa'eed Meshkin Fam
Abstract
Contractor evaluation and selection is one of the most important decision making problems that many regulations and methods have been introduced for it. In Iran, "Planning and Management Organization" is responsible for classification and prequalification of contractors and due to this responsibility, ...
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Contractor evaluation and selection is one of the most important decision making problems that many regulations and methods have been introduced for it. In Iran, "Planning and Management Organization" is responsible for classification and prequalification of contractors and due to this responsibility, this organization edit the Contractors Classification and Prequalification Regulation regularly. This regulation should be applied in Public sector and project owners should fulfill their tenders with respect to the article of tenders by law. In general, the current system is a multistage process in which, the best contractor will be selected according to its propositional price for tenders, in final step. In this paper, a multi criteria decision making model is introduced which can consider all of quantitative and qualitative factors that may affect on contractor selection in tenders. Six general criteria are considered in this model as the most effective factors on selecting a contractor; some of these criteria have their own sub criteria. A Fuzzy MADM method (by using linguistic variables) is used to rank the contractors and to select the best contractor in tenders.
Mahmoud Saffarzadeh; Vahid Abolhassan Nejad; Amin Mirza Boroujerdian
Abstract
One of the most important and effective factors in prioritizing high accident prone segments of roads for pedestrians is accident cause which up to now has been neglected in current methods. Since accidents are not additives due to various reasons, prioritizing these segments without considering the ...
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One of the most important and effective factors in prioritizing high accident prone segments of roads for pedestrians is accident cause which up to now has been neglected in current methods. Since accidents are not additives due to various reasons, prioritizing these segments without considering the accident cause makes the selection of high accident prone segments inaccurate. In this paper, by introducing the "Cause prioritizing model", a new model was developed in order to rank high accident prone segments for pedestrians with regard to accident cause in rural roads. In this method, by taking the accident frequency, accident severity and accident cause parameters are accounted and using one of the Multi Attribute Decision Making methods, the mentioned segments are prioritized. Using the model developed in this research will increase the accuracy and utility of high accident prone segments prioritizing process for pedestrians to a great extent.
