scholarly journals Residential choice from a multiple criteria sustainable perspective

Author(s):  
V. Liern ◽  
B. Pérez-Gladish ◽  
F. Rubiera-Morollón ◽  
B. M’Zali

AbstractMinimizing travel in the urban environment facilitates the development of sustainable cities. A key aspect is that there is a wide supply of amenities and facilities in the neighbourhoods: if most of the needs of families, goods and services can be covered from the sub-centers of the residential areas, it will be possible to reduce daily intra-urban mobility. The objective of this work is to propose a ranking multicriteria method that facilitates the choice of an ideal residential location in terms of neighbourhood characteristics, especially in the search of sustainable mobility for each family characteristics. One of the main problems in several Multiple Criteria Decision Making methods is the assignment of criteria weights in the aggregation process. The proposed methodology in this paper, Un-weighted TOPSIS (UW-TOPSIS) is able to overcome that problem. In this Multiple Criteria Decision Making (MCDM) method the relative proximity of each decision alternative to an ideal solution is minimized for the un-known weights of the criteria which are the variables in the corresponding mathematical programming program. Thus, a ranking based on the relative proximity of each alternative to an ideal alternative is obtained without the a priori establishment of the criteria weights. The use of subjective weights in real decision making contexts, where for instance a ranking of alternatives is required, is subject to important criticisms. This could be the case of the ranking of neighbourhoods based on their sustainability.

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1554
Author(s):  
Dragiša Stanujkić ◽  
Darjan Karabašević ◽  
Gabrijela Popović ◽  
Predrag S. Stanimirović ◽  
Muzafer Saračević ◽  
...  

The environment in which the decision-making process takes place is often characterized by uncertainty and vagueness and, because of that, sometimes it is very hard to express the criteria weights with crisp numbers. Therefore, the application of the Grey System Theory, i.e., grey numbers, in this case, is very convenient when it comes to determination of the criteria weights with partially known information. Besides, the criteria weights have a significant role in the multiple criteria decision-making process. Many ordinary multiple criteria decision-making methods are adapted for using grey numbers, and this is the case in this article as well. A new grey extension of the certain multiple criteria decision-making methods for the determination of the criteria weights is proposed. Therefore, the article aims to propose a new extension of the Step-wise Weight Assessment Ratio Analysis (SWARA) and PIvot Pairwise Relative Criteria Importance Assessment (PIPRECIA) methods adapted for group decision-making. In the proposed approach, attitudes of decision-makers are transformed into grey group attitudes, which allows taking advantage of the benefit that grey numbers provide over crisp numbers. The main advantage of the proposed approach in relation to the use of crisp numbers is the ability to conduct different analyses, i.e., considering different scenarios, such as pessimistic, optimistic, and so on. By varying the value of the whitening coefficient, different weights of the criteria can be obtained, and it should be emphasized that this approach gives the same weights as in the case of crisp numbers when the whitening coefficient has a value of 0.5. In addition, in this approach, the grey number was formed based on the median value of collected responses because it better maintains the deviation from the normal distribution of the collected responses. The application of the proposed approach was considered through two numerical illustrations, based on which appropriate conclusions were drawn.


2014 ◽  
Vol 55 ◽  
Author(s):  
Aleksandras Krylovas ◽  
Natalja Kosareva

The proposed in the article weights balancing approach enables to solve multiple criteria decision making tasks for the cases when objects are estimated by the two or more groups of the criteria which are not quantitatively compatible with each other. Criteria weights are being balanced by solving conditional optimization problems. The conditions for the certain optimization problem are determined by the construction of Kemeny median.


1993 ◽  
Vol 23 (2) ◽  
pp. 151-158 ◽  
Author(s):  
Andrew F. Howard ◽  
John D. Nelson

A new, deterministic methodology for simultaneous solution of the scheduling and allocation problems based on methods developed for multiple-criteria decision making is proposed. Seven steps for the use of multiple-criteria decision making techniques are reviewed, and the details of the proposed application to area-based harvest scheduling and forest land allocation are presented. The approach was used in a sample, hypothetical problem in which harvest schedules and allocations were developed for three competitors, using three decision criteria and two sets of criteria weights. The results indicate that the new method provides an effective alternative to traditional methods and offers numerous advantages including the explicit consideration of multiple objectives.


2016 ◽  
Vol 15 (05) ◽  
pp. 1157-1179 ◽  
Author(s):  
N. Thillaigovindan ◽  
S. Anita Shanthi ◽  
J. Vadivel Naidu

This paper considers a multiple criteria decision-making (MCDM) problem under risk in fuzzy environment in its general form. There are m alternatives which need to be ranked on the basis of a set of n criteria. The alternatives and the criteria are evaluated based on a set of l characteristics. The entire data is presented in the form of interval valued intuitionistic fuzzy soft set of root type. In addition each criterion is assigned a subjective criterion weight based on expert’s evaluation and each characteristic is assigned a probability weight on the basis of decision maker’s knowlege and understanding of the importance of the characteristic. This problem may be called as a MCDM problem under risk in fuzzy environment in its general form. A method for ranking the alternatives using the new score functions, prospect theory and method of determining the optimum criteria weights is explained. An algorithm is developed for this purpose and its working illustrated with a suitable example.


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