A review of application of multi-criteria decision making methods in construction

Construction is an area of study wherein making decisions adequately can mean the difference between success and failure. Moreover, most of the activities belonging to this sector involve taking into account a large number of conflicting aspects, which hinders their management as a whole. Multi-criteria decision making analysis arose to model complex problems like these. This paper reviews the application of 22 different methods belonging to this discipline in various areas of the construction industry clustered in 11 categories. The most significant methods are briefly discussed, pointing out their principal strengths and limitations. Furthermore, the data gathered while performing the paper are statistically analysed to identify different trends concerning the use of these techniques. The review shows their usefulness in characterizing very different decision making environments, highlighting the reliability acquired by the most pragmatic and widespread methods and the emergent tendency to use some of them in combination

Decision support model for the selection of asphalt wearing courses in highly trafficked roads

The suitable choice of the materials forming the wearing course of highly trafficked roads is a delicate task because of their direct interaction with vehicles. Furthermore, modern roads must be planned according to sustainable development goals, which is complex because some of these might be in conflict. Under this premise, this paper develops a multi-criteria decision support model based on the analytic hierarchy process and the technique for order of preference by similarity to ideal solution to facilitate the selection of wearing courses in European countries. Variables were modelled using either fuzzy logic or Monte Carlo methods, depending on their nature. The views of a panel of experts on the problem were collected and processed using the generalized reduced gradient algorithm and a distance-based aggregation approach. The results showed a clear preponderance by stone mastic asphalt over the remaining alternatives in different scenarios evaluated through sensitivity analysis. The research leading to these results was framed in the European FP7 Project DURABROADS (No. 605404).The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under Grant Agreement No. 605404

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

A stochastic multi-criteria assessment of security of transportation assets

Transportation project evaluation and prioritization use traditional performance measures including travel time, safety, user costs, economic efficiency, and environmental quality. The project impacts in terms of enhancing the infrastructure resilience or mitigating the consequences of infrastructure damage in the event of disaster occurrence are rarely considered in project evaluation. This dissertation presents a methodology to address this issue so that in evaluating and prioritizing investments, infrastructure with low security can receive the attention they deserve. Secondly, the methodology can be used for evaluating and prioritizing candidate investments dedicated specifically to security enhancement. In defining security as a function of threat likelihood, asset resilience and damage consequences, this dissertation uses security-related considerations in investment prioritization thus adding further robustness in traditional evaluations. As this leads to an increase in the number of performance criteria in the evaluation, the dissertation adopts a multiple-criteria analysis approach. The methodology quantifies the overall security level for an infrastructure in terms of the threats it faces, its resilience to damage, and the consequences in the event of the infrastructure damage. The dissertation demonstrates that it is feasible to develop a security-related measure that can be used as a performance criterion in the evaluation of general transportation projects or projects dedicated specifically towards security improvement. Through a case study, the dissertation applies the methodology by measuring the risk (and hence, security) of each for bridge infrastructure in Indiana. The method was also fuzzified and a Monte Carlo simulation was run to account for unknown data and uncertainty. On the basis of the multiple types of impacts including risk impacts such as the increase in security due to each candidate investment, this dissertation shows how to prioritize security investments across the multiple infrastructure assets using multiple-criteria analysis

A Multi-Criteria Methodology for Measuring the Resilience of Transportation Assets and Prioritizing Security Investments

Transportation project prioritization uses performance measures that are related to the transportation asset, its operations, and its environment. However, in the state of practice, evaluation does not consider directly the likelihood of natural or man-made threats, the infrastructure resilience, or the consequences of the infrastructure damage in the event that the threat occurs. Thus, during the prioritization of investments, assets of low security do not receive the due attention they deserve. In defining security as the lack of risk of damage from threats due to inherent structure or functional resilience, this paper is based on the premise that the inclusion of security considerations in prioritization introduces a much needed element of robustness in investment prioritization However, the inclusion of investment security impacts leads to an increase in the number of performance measures for the investment evaluation. This paper presents a methodology to quantify the overall security level for an asset in terms of the environmental threats it faces, its resilience or vulnerability to damage, and the consequences of the infrastructure damage. The overall framework consists of the traditional steps in risk management, and this paper\u27s specific contribution is in the part of the framework that measures the risk. This paper applies the methodology to a given set of assets by measuring the risk (security) of each asset and prioritizing security investments across multiple assets using multiple criteria analysis

Life Cycle Assessment of Bridges Using Bayesian Networks and Fuzzy Mathematics

[EN] At present, reducing the impact of the construction industry on the environment is the key to achieving sustainable development. Countries all over the world are using software systems for bridge environmental impact assessment. However, due to the complexity and discreteness of environmental factors in the construction industry, they are difficult to update and determine quickly, and there is a phenomenon of data missing in the database. Most of the lost data are optimized by Monte Carlo simulation, which greatly reduces the reliability and accuracy of the research results. This paper uses Bayesian advanced fuzzy mathematics theory to solve this problem. In the research, a Bayesian fuzzy mathematics evaluation and a multi-level sensitivity priority discrimination model are established, and the weights and membership degrees of influencing factors were defined to achieve comprehensive coverage of influencing factors. With the support of theoretical modelling, software analysis and fuzzy mathematics theory are used to comprehensively evaluate all the influencing factors of the five influencing stages in the entire life cycle of the bridge structure. The results show that the material manufacturing, maintenance, and operation of the bridge still produce environmental pollution; the main source of the emissions exceeds 53% of the total emissions. The effective impact factor reaches 3.01. At the end of the article, a big data sensitivity model was established. Through big data innovation and optimization analysis, traffic pollution emissions were reduced by 330 tonnes. Modeling of the comprehensive research model; application; clearly confirms the effectiveness and practicality of the Bayesian network fuzzy number comprehensive evaluation model in dealing with uncertain factors in the evaluation of the sustainable development of the construction industry. The research results have made important contributions to the realization of the sustainable development goals of the construction industry.This research was funded by the Spanish Ministry of Economy and Competitiveness, along with FEDER (Fondo Europeo de Desarrollo Regional), project grant number: BIA2017-85098-RZhou, Z.; Alcalá-González, J.; Kripka, M.; Yepes, V. (2021). Life Cycle Assessment of Bridges Using Bayesian Networks and Fuzzy Mathematics. Applied Sciences. 11(11):1-31. https://doi.org/10.3390/app11114916S131111

Uncertainty analysis methods to select the optimal alternative in the design of parking facilities

The selection of the preferred alternative in a parking facility project is usually made in a state of uncertainty. Decision-making methods are a useful tool to systematically arrive at a final decision between different alternatives and reduce subjectivity in decision making by creating a series of filters. However, the selection of the appropriate variables to be considered in the analysis may be problematic as well. Performing sensitivity analyses on entry variables is a key feature to ensure that the final choice is stable when initial conditions experience changes. This paper suggests a methodology to select the best alternative when considering parking facilities. The methodology compares the results from two different sensitivity analyses techniques. The changes in preference experienced as the applied weights change through the process are analyzed and the most critical criteria are identified

ODABIR MANAGERA KONTROLE KVALITETE NA OSNOVI AHP-COPRAS-G METODA: SLUČAJ U IRANU

Due to the increasing competition of globalization and fast technological improvements and world markets, demands of companies to have professional human resources are increasing too. It is an important problem of an organization to select the most appropriate personnel among the candidates. Quality control manager is important personnel in organizations and it’s so important to select the best candidate for this work. In this paper we proposed a personnel selection system based on Analytic Hierarchy Process (AHP) and Complex proportional assessment of alternatives with grey relations (COPRAS-G) method. At first seven criteria is identified including: knowledge of product and raw material properties, Experience and educational background, Administrative orientation, Behavioral flexibility, Risk evaluation ability, Payment and Team work and after that AHP applied for calculating weight of each criteria and finally using COPRAS- G method for selecting the best candidate for this job. This study can be used as a pattern for personnel selection and future researches.S obzirom na rastuću konkurentnost u globalizaciji te brzim tehnološkim napredovanjem na svjetskom tržištu, zahtjevi kompanija za profesionalnim kadrom se također povećavaju. Vrlo je važno za organizaciju biti u mogućnosti odabrati najbolji i najprimjereniji kadar među ponuđenim kandidatima. Manager kontrole kvalitete je važan kadar u bilo kojoj organizaciji tako da je iznimno važno za taj posao odabrati najbolje kandidate. U ovom radu predlažemo sustav odabira kadra zasnovan na analitičkom hijerarhijskom procesu (AHP) i kompleksnoj proporcionalnoj evaluaciji alternativa sa sivim odnosima (COPRAS-G). Isprva je identificirano sedam kriterija uključujući: znanje o proizvodu i svojstvima sirovine, iskustvo i obrazovanje, snalaženje s administracijom, fleksibilnost u ponašanju, sposobnost procjene rizika, plaćanja i timski rad te je zatim primijenjen AHP za izračunavanje težine svakog kriterija te je naposljetku korištena COPRAS-G metoda za odabir najboljih kandidata. Ova studija se može koristiti kao predložak za odabir kandidata i buduća istraživanja

Neutrosophic Completion Technique for Incomplete Higher-Order AHP Comparison Matrices

[EN] After the recent establishment of the Sustainable Development Goals and the Agenda 2030, the sustainable design of products in general and infrastructures in particular emerge as a challenging field for the development and application of multicriteria decision-making tools. Sustainability-related decision problems usually involve, by definition, a wide variety in number and nature of conflicting criteria, thus pushing the limits of conventional multicriteria decision-making tools practices. The greater the number of criteria and the more complex the relations existing between them in a decisional problem, the less accurate and certain are the judgments required by usual methods, such as the analytic hierarchy process (AHP). The present paper proposes a neutrosophic AHP completion methodology to reduce the number of judgments required to be emitted by the decision maker. This increases the consistency of their responses, while accounting for uncertainties associated to the fuzziness of human thinking. The method is applied to a sustainable-design problem, resulting in weight estimations that allow for a reduction of up to 22% of the conventionally required comparisons, with an average accuracy below 10% between estimates and the weights resulting from a conventionally completed AHP matrix, and a root mean standard error below 15%.The authors acknowledge the financial support of the Spanish Ministry of Economy and Business, along with FEDER funding (DIMALIFE Project: BIA2017-85098-R).Navarro, IJ.; Martí Albiñana, JV.; Yepes, V. (2021). Neutrosophic Completion Technique for Incomplete Higher-Order AHP Comparison Matrices. Mathematics. 9(5):1-19. https://doi.org/10.3390/math905049611995Worrell, E., Price, L., Martin, N., Hendriks, C., & Meida, L. O. (2001). CARBON DIOXIDE EMISSIONS FROM THE GLOBAL CEMENT INDUSTRY. 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Experimental study of heat transfer enhancement by inserting metal chain in heat exchanger tube

Heat transfer augmentation in heat exchangers is important in many large industrial applications and many studies have been conducted on this subject. In this paper, an experimental study was used to verify the increased heat transfer of a circular heat exchanger tube with the insertion of metal chains, under turbulent flow conditions. A rig was designed and fabricated to investigate the effects of using the metal chain as turbulators inside the heat exchanger pipe, on heat transfer performance and on fluid flow behavior. The metal chains used were of different lengths of chain ring and different diameters of ring wire. Five ring length/tube diameter ratios (P/D) were used, (1, 2, 3, 4 and 5). Two wire diameter /tube diameter ratios (t/D) were used in this work (0.1 and 0.15). Heavy fuel oil (HFO) was used inside the tube, flowing at 30 °C with uniform tube wall temperature. The Reynolds numbers tested were between 5,000 and 15,000. The results showed the thermal enhancement factor (η) decreased with increasing Reynolds number for all cases, depending on lengths of chain ring (P) and thickness the weir chain (t) values. A maximum thermal enhancement factor (η) was found with a metal chain at P/D=3 and t/D= 0.15. The results also show that P/D=1 and t= 4mm, give the highest Nusselt number