Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

Synthetic rating system for railway bridge management

Railway bridges deteriorate with age. Factors such as environmental effects on different materials of a bridge, variation of loads, fatigue, etc will reduce the remaining life of bridges. Bridges are currently rated individually for maintenance and repair actions according to the structural conditions of their elements. Dealing with thousands of bridges and several factors that cause deterioration, makes the rating process extremely complicated. Current simplified but practical rating methods are not based on an accurate structural condition assessment system. On the other hand, the sophisticated but more accurate methods are only used for a single bridge or particular types of bridges. It is therefore necessary to develop a practical and accurate system which will be capable of rating a network of railway bridges. This paper introduces a new method for rating a network of bridges based on their current and future structural conditions. The method identifies typical bridges representing a group of railway bridges. The most crucial agents will be determined and categorized to criticality and vulnerability factors. Classification based on structural configuration, loading, and critical deterioration factors will be conducted. Finally a rating method for a network of railway bridges that takes into account the effects of damaged structural components due to variations in loading and environmental conditions on the integrity of the whole structure will be proposed. The outcome of this research is expected to significantly improve the rating methods for railway bridges by considering the unique characteristics of different factors and incorporating the correlation between them

Classification of railway bridges based on criticality and vulnerability factors

Bridges are currently rated individually for maintenance and repair action according to the structural conditions of their elements. Dealing with thousands of bridges and the many factors that cause deterioration, makes this rating process extremely complicated. The current simplified but practical methods are not accurate enough. On the other hand, the sophisticated, more accurate methods are only used for a single or particular bridge type. It is therefore necessary to develop a practical and accurate rating system for a network of bridges. The first most important step in achieving this aim is to classify bridges based on the differences in nature and the unique characteristics of the critical factors and the relationship between them, for a network of bridges. Critical factors and vulnerable elements will be identified and placed in different categories. This classification method will be used to develop a new practical rating method for a network of railway bridges based on criticality and vulnerability analysis. This rating system will be more accurate and economical as well as improve the safety and serviceability of railway bridges

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

Multicriteria decision making for enhanced perception-based multimedia communication

This paper proposes an approach that integrates technical concerns with user perceptual considerations for intelligent decision making in the construction of tailor-made multimedia communication protocols. Thus, the proposed approach, based on multicriteria decision making (MDM), incorporates not only classical networking considerations, but, indeed, user preferences as well. Furthermore, in keeping with the task-dependent nature consistently identified in multimedia scenarios, the suggested communication protocols also take into account the type of multimedia application that they are transporting. Lastly, this approach also opens the possibility for such protocols to dynamically adapt based on a changing operating environment and user's preferences

Reliability Improvement On Feasibility Study For Selection Of Infrastructure Projects Using Data Mining And Machine Learning

With the progressive development of infrastructure construction, conventional analytical methods such as correlation index, quantifying factors, and peer review are no longer satisfactory in support for decision-making of implementing an infrastructure project in the age of big data. This study proposes using a mathematical model named Fuzzy-Neural Comprehensive Evaluation Model (FNCEM) to improve the reliability of the feasibility study of infrastructure projects by using data mining and machine learning. Specifically, the data collection on time-series data, including traffic videos (278 Gigabytes) and historical weather data, uses transportation cameras and online searching, respectively. Meanwhile, the researcher sent out a questionnaire for the collection of the public opinions upon the influencing factors that an infrastructure project may have. Then, this model implements the backpropagation Artificial Neural Network (BP-ANN) algorithm to simulate traffic flows and generate outputs as partial quantitative references for evaluation. The traffic simulation outputs used as partial inputs to the Analytic Hierarchy Process (AHP) based Fuzzy logic module of the system for the determination of the minimum traffic flows that a construction scheme in corresponding feasibility study should meet. This study bases on a real scenario of constructing a railway-crossing facility in a college town. The research results indicated that BP-ANN was well applied to simulate 15-minute small-scale pedestrian and vehicle flow with minimum overall logarithmic mean squared errors (Log-MSE) of 3.80 and 5.09, respectively. Also, AHP-based Fuzzy evaluation significantly decreased the evaluation subjectivity of selecting construction schemes by 62.5%. It concluded that the FNCEM model has strong potentials of enriching the methodology of conducting a feasibility study of the infrastructure project

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

Safety Grade Evaluation of Aqueduct Structure Based on Fuzzy Cloud Theory Analysis

In view of the limitation of natural conversion between qualitative concept and quantitative value, the fuzzy analysis method cannot be employed to improve the multi-stage fuzzy evaluation method. Improvement of multilevel fuzzy evaluation method based on cloud theory was found, which could comprehensively consider the uncertainty of random combinations and the fuzziness of interaction between influencing factors, and the shortcomings of conventional fuzzy evaluation methods as well eliminated. The structure of 5#U-aqueduct in Jingdian Irrigation District (Gansu, China) was chosen as the research object. Based on the multi-level fuzzy evaluation index system of structural safety, experts were invited to score the importance of factors according to the cloud theory scale criterion to establish a judgment matrix. Therefore, the evaluation set, weight and membership cloud model of evaluation system was constituted by means of bridge safety assessment criterion and cloud generator principle. Furthermore, comprehensive evaluation results of aqueduct service states were obtained by multistage fuzzy composite mapping method, and the actual position of structural safety grade was obtained by comparing the evaluation result with the comment layer cloud drop diagram. The results showed that using cloud model parameters (Ex, En and He) to describe the relative importance of factors can better reflect the randomness and fuzziness of each other than the traditional single number, which was helpful to get the evaluation results accurately and objectively; The comprehensive evaluation results of the aqueduct structure obtained by calculation were WV(75.149, 9.95, 4.16).The simulated cloud droplet diagram was located between II and III classes, and tends to the III standard, which indicated that the overall security of the structure was sufferable. However, attention should be paid to the maintenance and repair of the detailed components. The consequences agreed with the evaluation results of the experts, which indicates that the improved evaluation method has good practicability as well as can be popularized and applied