Evaluation of new service concepts using rough set theory and group analytic hierarchy process

In order to study the influence of human body parts on the overall comfort under different sports conditions, this paper designed a series of actions such as standing, squatting, running, walking, and so on, and obtained the key parts that affected the overall comfort at every experimental stage (i.e. every motion state) through subjective evaluation. That is, to study and analyze the comfort evaluation of every part and the whole body under different motions conditions, as well as the main parts that affect the overall comfort. In this paper, Analytic Hierarchy Process-Entropy weight, Fuzzy-Rough Set Theory, Analytic Hierarchy Process-Structural Equation Model, and Particle Swarm Optimization-Cuckoo Search were used to optimize the position index. At last, the prediction model of overall comfort was established by Adaptive Network-based Fuzzy Influence System. The input parameters are body part indexes screened by Analytic Hierarchy Process-Entropy weight, Fuzzy-Rough Set Theory, Analytic Hierarchy Process-Structural Equation Model and Particle Swarm Optimization-Cuckoo Search, respectively. And the output is the overall comfort evaluation value. Compared with the real value of overall comfort in every experimental stage, the effectiveness of Analytic Hierarchy Process-Entropy weight, Fuzzy-Rough Set Theory, Analytic Hierarchy Process-Structural Equation Model, and Particle Swarm Optimization-Cuckoo Search optimizing indexes is verified. The results show that: (1) About index optimization models, Particle Swarm Optimization-Cuckoo Search and Analytic Hierarchy Process-Entropy weight are better than Fuzzy-Rough Set Theory, so both Particle Swarm Optimization-Cuckoo Search and Analytic Hierarchy Process-Entropy weight could optimize index predicting overall comfort. (2) Different movements have great differences in the parts that affect the overall comfort.

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Analysis of time overruns in roads and highways sector in India using AHP ranking technique

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i3.29.18807 ◽

2018 ◽

Vol 7 (3.29) ◽

pp. 259

Author(s):

Siddesh K. Pai ◽

Avinash Kumar Singh ◽

Ankur Mittal ◽

Neeraj Anand

Keyword(s):

Decision Making ◽

Analytic Hierarchy Process ◽

Set Theory ◽

Fuzzy Set ◽

Fuzzy Set Theory ◽

Analytic Hierarchy ◽

Severity Factor ◽

Construction Firm ◽

The Right ◽

Hierarchy Process

In today’s scenario there will be a competition exists among various construction firm, so the risk management come into picture to assess the various risk related to project. Assigning the right severity factor as per the possibility of occurrence will impart the success of organization as well as success will impart the growth of nation with increase in G.D.P. In construction of road the assessment of right severity factor, will be considered as strength to lower down the delay of time over run. Tremendous amount of effort are applied in quantitative and qualitative manner for assessment of risk severity factor. However, many criteria for risk severity factor enable the decision making methods will smoothen the process of arriving at a solution and enable decision makers to make the right decisions. Decision-making problems need systematic approach to appraise the various alternatives using quantitative and non quantitative factors. Standard methods for solving problems will lack considerations of non-quantitative factors, where numeric values are difficult to assign. Different techniques like, Analytic Hierarchy Process (AHP), Fuzzy set theory Making and Multi Criteria Decision are being used in risk severity factor. These techniques consider factors with concrete values or vague values. This research will provide solution to a risk severity factor for budget allocation problem, for allocating funds to competing and deserving organizations by using ranking analysis technique. Fuzzy set theory and AHP is used to calculate the Weights .Fuzzy set considers subjective values like preferred, strongly preferred etc. and Analytic Hierarchy Process (AHP) technique evaluates relative importance of factors by making pair wise comparison matrix. The evaluation technique will facilitate in ranking of various severity factors according to their possibility of occurrence after assigning weights to decision making factor.

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