Inicio  /  Algorithms  /  Vol: 14 Par: 5 (2021)  /  Artículo
ARTÍCULO
TITULO

PROMETHEE-SAPEVO-M1 a Hybrid Approach Based on Ordinal and Cardinal Inputs: Multi-Criteria Evaluation of Helicopters to Support Brazilian Navy Operations

Miguel Ângelo Lellis Moreira    
Igor Pinheiro de Araújo Costa    
Maria Teresa Pereira    
Marcos dos Santos    
Carlos Francisco Simões Gomes and Fernando Martins Muradas    

Resumen

This paper presents a new approach based on Multi-Criteria Decision Analysis (MCDA), named PROMETHEE-SAPEVO-M1, through its implementation and feasibility related to the decision-making process regarding the evaluation of helicopters of attack of the Brazilian Navy. The proposed methodology aims to present an integration of ordinal evaluation into the cardinal procedure from the PROMETHEE method, enabling to perform qualitative and quantitative data and generate the criteria weights by pairwise evaluation, transparently. The modeling provides three models of preference analysis, as partial, complete, and outranking by intervals, along with an intra-criterion analysis by veto threshold, enabling the analysis of the performance of an alternative in a specific criterion. As a demonstration of the application, is carried out a case study by the PROMETHEE-SAPEVO-M1 web platform, addressing a strategic analysis of attack helicopters to be acquired by the Brazilian Navy, from the need to be evaluating multiple specifications with different levels of importance within the context problem. The modeling implementation in the case study is made in detail, first performing the alternatives in each criterion and then presenting the results by three different models of preference analysis, along with the intra-criterion analysis and a rank reversal procedure. Moreover, is realized a comparison analysis to the PROMETHEE method, exploring the main features of the PROMETHEE-SAPEVO-M1. Moreover, a section of discussion is presented, exposing some features and main points of the proposal. Therefore, this paper provides a valuable contribution to academia and society since it represents the application of an MCDA method in the state of the art, contributing to the decision-making resolution of the most diverse real problems.

 Artículos similares

       
 
Aravind Kolli, Qi Wei and Stephen A. Ramsey    
In this work, we explored computational methods for analyzing a color digital image of a wound and predicting (from the analyzed image) the number of days it will take for the wound to fully heal. We used a hybrid computational approach combining deep ne... ver más
Revista: Computation

 
Mattia Neroni, Massimo Bertolini and Angel A. Juan    
In automated storage and retrieval systems (AS/RSs), the utilization of intelligent algorithms can reduce the makespan required to complete a series of input/output operations. This paper introduces a simulation optimization algorithm designed to minimiz... ver más
Revista: Algorithms

 
Ruslans Babajans, Darja Cirjulina, Filips Capligins, Deniss Kolosovs and Anna Litvinenko    
The current work is focused on studying the performance of the Pecora?Carroll synchronization technique to achieve synchronization between the analog and discrete chaos oscillators. The importance of this study is supported by the growing applications of... ver más
Revista: Applied Sciences

 
Waseem Abbas, Zuping Zhang, Muhammad Asim, Junhong Chen and Sadique Ahmad    
In the ever-expanding online fashion market, businesses in the clothing sales sector are presented with substantial growth opportunities. To utilize this potential, it is crucial to implement effective methods for accurately identifying clothing items. T... ver más
Revista: Information

 
Muhammad Sheraz, Teong Chee Chuah, Mardeni Bin Roslee, Manzoor Ahmed, Amjad Iqbal and Ala?a Al-Habashna    
Data caching is a promising technique to alleviate the data traffic burden from the backhaul and minimize data access delay. However, the cache capacity constraint poses a significant challenge to obtaining content through the cache resource that degrade... ver más
Revista: Applied Sciences