Analysis on fuzzy decision-making of foundation pit support system based on improved Analytic Hierarchy Process

Author(s):  
Ying Liao
Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 1037
Author(s):  
Jan Hodicky ◽  
Gökhan Özkan ◽  
Hilmi Özdemir ◽  
Petr Stodola ◽  
Jan Drozd ◽  
...  

Resilience is a complex system that represents dynamic behaviours through its complicated structure with various nodes, interrelations, and information flows. Like other international organizations NATO has also been dealing with the measurement of this complex phenomenon in order to have a comprehensive understanding of the civil environment and its impact on military operations. With this ultimate purpose, NATO had developed and executed a prototype model with the system dynamics modelling and simulation paradigm. NATO has created an aggregated resilience model as an upgrade of the prototype one, as discussed within this study. The structure of the model, aggregation mechanism and shock parametrization methodologies used in the development of the model comprise the scope of this study. Analytic Hierarchy Process (AHP), which is a multi-criteria decision-making technique is the methodology that is used for the development of the aggregation mechanism. The main idea of selecting the AHP methodology is its power and usefulness in mitigating bias in the decision-making process, its capability to increase the number of what-if scenarios to be created, and its contribution to the quality of causal explanations with the granularity it provides. The parametrized strategic shock input page, AHP-based weighted resilience and risk parameters input pages, one more country insertion to the model, and the decision support system page enhance the capacity of the prototype model. As part of the model, the decision support system page stands out as the strategic level cockpit where the colour codes give a clear idea at first about the overall situational picture and country-wise resilience and risk status. At the validation workshop, users not only validated the model but also discussed further development opportunities, such as adding more strategic shocks into the model and introduction of new parameters that will be determined by a big data analysis on relevant open source databases. The developed model has the potential to inspire high-level decision-makers dealing with resilience management in other international organizations, such as the United Nations.


2021 ◽  
Vol 13 (16) ◽  
pp. 9067
Author(s):  
Dominika Siwiec ◽  
Andrzej Pacana

Dynamic changes in customers’ expectations and unfavorable climate changes have generated the need to consider such aspects in the process of creating new products and the modernization of existing products. Simultaneously including customers’ expectations and environmental impact is a key element of the sustainable development of products. Enterprises attempt, within their awareness and possibilities, to apply the idea of sustainability; they do this more or less methodically. As such, an instrument to support decision-making in the area of product development is still needed because it would both be desirable for customers and have less of a negative effect on the natural environment. The purpose of this study was to develop a model that supports decision-making in the development of products while considering sustainability. The model determines the key criteria of the product, criteria states (current and future), and their positive correlations (e.g., achieving high levels of product quality and no (or a reduction in) destructive impact on the environment). To reduce the fuzzy decision-making environment, multiplicative decision methods with the fuzzy Saaty scale were implemented. These methods were the fuzzy analytic hierarchy process (FAHP) and the fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS). The model is able to support qualitative–environment decisions in the development of any product.


2014 ◽  
Vol 989-994 ◽  
pp. 2588-2592
Author(s):  
Bing Jiang Zhang

In this paper, we suggest and analyze a new support system for easy decision-making on housing planning. Using this, user’s can analyze their preferences by themselves individually and can select optimal alternatives. The purpose of this paper is to propose a rational decision-making system in housing planning based on the ASP (Analytic Hierarchy Process). Then, we show how standard evaluation can be decided on this system. In this paper, evaluation and election of the room arrangements is based on the information data came from users.


2016 ◽  
Vol 1 (1) ◽  
pp. 088
Author(s):  
Wahyu Joni Kurniawan

This study was conducted to assist in the selection of martial assistant coach, to determine who is right. Its results will didadaptkan by comparing the two methods in the decision support system, by using the Analytic Hierarchy Process (AHP) and the Simple Additive Weight (SAW) in limiting the problems in producing the desired solution, using multiple criteria (multi-criteria). AHP and SAW has a different way of doing the calculation. This is done to determine which method is looking for help in making decisions. And in this study are the criteria Discipline, Knowledge, Leadership, Attitude, and Level. And there are sub criteria on Level, which Black (AND I) and Red Black II.


Author(s):  
G. Marimuthu ◽  
G. Ramesh

Decisions usually involve the getting the best solution, selecting the suitable experiments, most appropriate judgments, taking the quality results etc., using some techniques.  Every decision making can be considered as the choice from the set of alternatives based on a set of criteria.  The fuzzy analytic hierarchy process is a multi-criteria decision making and is dealing with decision making problems through pairwise comparisons mode [10].  The weight vectors from this comparison model are obtained by using extent analysis method.  This paper concern with an alternate method of finding the weight vectors from the original fuzzy AHP decision model (moderate fuzzy AHP model), that has the same rank as obtained in original fuzzy AHP and ideal fuzzy AHP decision models.


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