scholarly journals Application of Multicriteria Decision Making and Multi-Objective Planning Methods for Evaluating Metropolitan Parks in Terms of Budget and Benefits

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1304 ◽  
Author(s):  
Wen-Chi Lo ◽  
Ching-Hua Lu ◽  
Ying-Chyi Chou
Keyword(s):  
Decision Making ◽  
Resource Utilization ◽  
De Novo ◽  
Social Indicators ◽  
Multicriteria Decision Making ◽  
Developed Countries ◽  
Multicriteria Decision ◽  
Multi Objective ◽  
Planning Methods ◽  
The Impact

Urbanization is inevitable in developed countries. This study investigated the design of metropolitan parks, which are essential for sustainable cities. The developed model examined the suitability of parks in Taichung City, Taiwan, and explored the three aspects of ecological, economic, and social indicators for park design using De Novo planning tools and the Decision Making Trial and Evaluation Laboratory-based Analytic Network Process. Because the De Novo programming method can redesign budget restrictions, this method can help managers arrange budget programming and reduce the impact of excessive investment on resource utilization in specific projects. After obtaining each factor’s price, the De Novo planning approach can reduce economic and ecological resource input and improve benefits relative to existing resource utilization methods. When assuming a fixed investment of resources, the De Novo planning method moves resources from the economic and ecological aspects of leisure and recreation, thus increasing the total benefit of metropolitan parks. Multicriteria decision-making and multi-objective planning methods can provide an effective solution for evaluating metropolitan parks.

Integrated data envelopment analysis and multicriteria decision-making ranking approach based on peer-evaluations and subjective preferences: case study in banking sector

2020 ◽  
Vol 54 (4) ◽  
pp. 551-582
Author(s):  
Jolly Puri ◽  
Meenu Verma
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Decision Maker ◽  
Multicriteria Decision Making ◽  
Peer Evaluation ◽  
Data Envelopment ◽  
Content Type ◽  
Multicriteria Decision ◽  
Subjective Preference ◽  
The Impact

PurposeThis paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking decision-making units (DMUs) based on cross-efficiency technique and subjective preference(s) of the decision maker.Design/methodology/approachSelf-evaluation in data envelopment analysis (DEA) lacks in discrimination power among DMUs. To fix this, a cross-efficiency technique has been introduced that ranks DMUs based on peer-evaluation. Different cross-efficiency formulations such as aggressive and benevolent and neutral are available in the literature. The existing ranking approaches fail to incorporate subjective preference of “one” or “some” or “all” or “most” of the cross-efficiency evaluation formulations. Therefore, the integrated framework in this paper, based on DEA and multicriteria decision-making (MCDM), aims to present a ranking approach to incorporate different cross-efficiency formulations as well as subjective preference(s) of decision maker.FindingsThe proposed approach has an advantage that each of the aggressive, benevolent and neutral cross-efficiency formulations contribute to select the best alternative among the DMUs in a MCDM problem. Ordered weighted averaging (OWA) aggregation is applied to aggregate final cross-efficiencies and to achieve complete ranking of the DMUs. This new approach is further illustrated and compared with existing MCDM approaches like simple additive weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prove its validity in real situations.Research limitations/implicationsThe choice of cross-efficiency formulation(s) as per subjective preference of the decision maker and different orness levels lead to different aggregated scores and thus ranking of the DMUs accordingly. The proposed ranking approach is highly useful in real applications like R and D projects, flexible manufacturing systems, electricity distribution sector, banking industry, labor assignment and the economic environmental performances for ranking and benchmarking.Practical implicationsTo prove the practical applicability and robustness of the proposed integrated DEA-MCDM approach, it is applied to top twelve Indian banks in terms of three inputs and two outputs for the period 2018–2019. The findings of the study (1) ensure the impact of non-performing assets (NPAs) on the ranking of the selected banks and (2) are enormously valuable for the bank experts and policy makers to consider the impact of peer-evaluation and subjective preference(s) in formulating appropriate policies to improve performance and ranks of underperformed banks in competitive scenario.Originality/valueTo the best of the authors’ knowledge, this is the first study that has integrated both DEA and MCDM via OWA aggregation to present a ranking approach that can incorporate different cross-efficiency formulations and subjective preference(s) of the decision maker for ranking DMUs.

Analysis of the impact of attitudinal character on the multicriteria decision making with OWA operators

2012 ◽  
Vol 27 (5) ◽  
pp. 502-518 ◽  
Author(s):  
Feng-Mei Ma ◽  
Ya-Jun Guo ◽  
Xiang Shan
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Multicriteria Decision ◽  
Owa Operators ◽  
The Impact

scholarly journals Selection Method for Kernel Function in Nonparametric Extrapolation Based on Multicriteria Decision-Making Technology

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Jixin Wang ◽  
Yan Liu ◽  
Xiaohua Zeng ◽  
Zhenping Zhou ◽  
Naixiang Wang ◽  
...  
Keyword(s):  
Decision Making ◽  
Kernel Function ◽  
Maximum Entropy Principle ◽  
Multicriteria Decision Making ◽  
Selection Method ◽  
Entropy Method ◽  
Kernel Functions ◽  
Load Spectrum ◽  
Multicriteria Decision ◽  
The Impact

Selecting the most appropriate kernel function to extrapolate a load set is the paramount step in compiling load spectrum, as it affects the results of nonparametric extrapolation largely. Aiming at this issue, this paper provides a new approach in selecting kernel function for the nonparametric extrapolation. To solve the complexity and uncertainty of nonparametric extrapolation, characteristics of four kernel functions and their effects on the results are explained in the “from-to” diagram obtained by rainflow counting. Multicriteria decision-making (MCDM) is then applied to solve the selection problem of kernel function. To evaluate the dispersion degrees of the mean and amplitude of a load set accurately, their range, standard deviation, and interquartile range are selected as the evaluation criteria. The weight of each criterion, which represents the impact degree on the selection of the kernel function, is calculated separately using the eigenvector and entropy method. The comprehensive weights are obtained by applying the optimization theory and Jaynes’ maximum entropy principle. Finally, the importance of each criterion is discussed according to their calculated comprehensive weights, and the selection method for kernel functions is obtained, which is illustrated by extrapolating the output torque of the power split device of hybrid electrical vehicles.

Assessing the Impact of Lean Tools on Production and Safety by a Multicriteria Decision-Making Model and Statistical Analysis: A Case Study in Textile Sector

2021 ◽  
pp. 616-638
Author(s):  
José Carlos Sá ◽  
Joni Pinto Jorge ◽  
Gilberto Santos ◽  
Maria João Félix ◽  
Luis Barreto ◽  
...  
Keyword(s):  
Decision Making ◽  
Statistical Analysis ◽  
Multicriteria Decision Making ◽  
Multicriteria Decision ◽  
Lean Tools ◽  
Decision Making Model ◽  
The Impact ◽  
Textile Sector

scholarly journals MULTIMOORA under Interval-Valued Neutrosophic Sets as the Basis for the Quantitative Heuristic Evaluation Methodology HEBIN

Mathematics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 66
Author(s):  
Edmundas Kazimieras Zavadskas ◽  
Romualdas Bausys ◽  
Ingrida Lescauskiene ◽  
Ana Usovaite
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Evaluation Methodology ◽  
Heuristic Evaluation ◽  
Neutrosophic Sets ◽  
Interval Numbers ◽  
Multicriteria Decision ◽  
Decision Methods ◽  
The Impact ◽  
Interval Valued

During the last decade, researchers put a lot of effort into the development of the multi-criteria decision methods (MCDM) capable of dealing with the uncertainty and vagueness of the initial information. MCDM approaches that work under the environment of the interval-valued neutrosophic sets (IVNS) demonstrate credibility for the analysis of different opinions as well as for the inconsistency of the criteria evaluation data. The novel multicriteria decision-making approach MULTIMOORA-IVNS (multi-objective optimisation by ratio analysis under interval-valued neutrosophic sets) is presented in this paper. A novel heuristic evaluation methodology HEBIN (heuristic evaluation based on interval numbers) that exploits MULTIMOORA-IVNS for the processing of the evaluation results is also presented in this research. HEBIN is able to increase the accuracy of the checklists-based heuristic evaluation and to diminish the impact of the inconsistencies caused by the evaluators. A comparison of six e-commerce websites is introduced to reveal the practicalities of the proposed multicriteria decision-making application.

scholarly journals Sustainability in the Business Sector: A Fuzzy Multicriteria Decision-Making Model for Financial Leasing Company Selection of the Vietnamese SMEs

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110360
Author(s):  
Fengsheng Chien ◽  
Chia-Nan Wang ◽  
Ka Yin Chau ◽  
Van Thanh Nguyen ◽  
Viet Tinh Nguyen
Keyword(s):  
Decision Making ◽  
Interest Rates ◽  
Small And Medium Enterprises ◽  
Multicriteria Decision Making ◽  
Primary Concern ◽  
Multicriteria Decision ◽  
Financial Leasing ◽  
Criteria Weights ◽  
Leasing Company ◽  
Selection Of

The uses and management of capital is extremely important to the operation of any businesses. However, not all businesses have available capital, so the use of loans in many different forms is always an effective solution in managing corporate finance. Accompanying with businesses, many financial leasing companies have implemented products and programs to lend money to businesses with low interest rates. So, choosing the best financial leasing company is a primary concern of businesses. To increase competitiveness, financial leasing companies often offer preferential conditions to attract businesses. Choosing the best financial leasing service to leasing is important and necessary to those businesses. Thus, the selection of a financial leasing company by small and medium enterprises benefits from the application of Multicriteria Decision-Making (MCDM) methods which allows the decision maker to consider various qualitative and quantitative criteria. In this article, the author applied Fuzzy Analytical Network Process (FANP) to calculate the related criteria weights of the financial leasing company selection problem of businesses. Then, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is applied to rank the potential decision-making units. This research establishes one complete and efficient model for financial leasing company selection using FANP and TOPSIS methods. The proposed model is then applied into a real-world case study to demonstrate its feasibility.

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