Using interval weights in MADM problems

The choice of weights vectors in multiple attribute decision making (MADM) problems has generated an important literature, and a large number of methods have been proposed for this task. In some situations the decision maker (DM) may not be willing or able to provide exact values of the weights, but this difficulty can be avoided by allowing the DM to give some variability in the weights. In this paper we propose a model where the weights are not fixed, but can take any value from certain intervals, so the score of each alternative is the maximum value that the weighted mean can reach when the weights belong to those intervals. We provide a closed-form expression for the scores achieved by the alternatives so that they can be ranked them without solving the proposed model, and apply this new method to an MADM problem taken from the literature.Este trabajo forma parte del proyecto de investigación: MEC-FEDER Grant ECO2016-77900-P

Comparison of two methods in multi-criteria decision-making: application in transmission rod material selection

Transmission rod is an indispensable part in diesel and gasoline engines. Its job is to convert rotation into translational motion or vice versa. The transmission rod material selection plays a very important role, affecting its working function and durability. This study was conducted to compare two Multi Criteria Decision Making (MCDM) methods in transmission rod material selection. They are PIV (Proximity Indexed Value) method, and FUCA (Faire Un Choi Adéquat) method. Seven types of steel commonly used in transmission rods were reviewed for ranking, inclusive of: 20 steel, 40 steel, 45 steel, 18Cr2Ni4WA steel, 30 CrMoA steel, 45Mn2 steel and 40CrNi steel. Nine parameters were used as criteria to evaluate each steel including minimum yield strength, ultimate tensile strength, minimum elongation ratio, contraction ratio, modulus of elasticity, mean coefficient of thermal expansion, thermal conductivity, specific thermal capacity, and density. The weights of the criteria were calculated using three methods inclusive of MEAN weight method, Entropy weight method and MEREC weight method (Method based on the Removal Effects of Criteria). Each MCDM method was combined with the three weight methods mentioned above to rank the alternatives. The obtained results show that when using both PIV and FUCA methods to rank the alternatives, the best and worst alternatives are found regardless of the weight of the criteria. The best alternative determined using the PIV method is also the best alternative determined using the FUCA method. It means that the two PIV and FUCA methods have been shown to be equally effective. Among the seven transmission rod materials reviewed, 20 steel was identified as the best, and 40CrNi steel was identified as the wors

Multi-Criteria Handover Using Modified Weighted TOPSIS Methods for Heterogeneous Networks

Ultra-dense small cell deployment in future 5G networks is a promising solution to the ever increasing demand of capacity and coverage. However, this deployment can lead to severe interference and high number of handovers, which in turn cause increased signaling overhead. In order to ensure service continuity for mobile users, minimize the number of unnecessary handovers and reduce the signaling overhead in heterogeneous networks, it is important to model adequately the handover decision problem. In this paper, we model the handover decision based on the multiple attribute decision making method, namely Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The base stations are considered as alternatives, and the handover metrics are considered as attributes to selecting the proper base station for handover. In this paper, we propose two modified TOPSIS methods for the purpose of handover management in the heterogeneous network. The first method incorporates the entropy weighting technique for handover metrics weighting. The second proposed method uses a standard deviation weighting technique to score the importance of each handover metric. Simulation results reveal that the proposed methods outperformed the existing methods by reducing the number of frequent handovers and radio link failures, in addition to enhancing the achieved mean user throughput

Distance Metrics Library for MCDA Methods

Information systems based on Multi-Criteria Decision Analysis (MCDA) methods enable considering multiple attributes with contrary objectives. Information systems using MCDA simplify and automatize assessment toward automatizing decision support systems. Individual MCDA methods differ in their algorithms, implying different results for the same problem. Moreover, the diversity of algorithms refers to the MCDA methods and their techniques used at an individual stage, such as distance metrics. They are implemented in MCDA methods to measure alternatives’ distances from reference solutions. The most commonly used metric is the Euclidean distance. However, other distance metrics are also suitable for this purpose. Moreover, a broad set of metrics can be helpful in comparative analysis to test the robustness of particular scenarios. Therefore, the main contribution of a Python library for multi-criteria decision analysis called distance-metrics-mcda is providing a set of 20 distance metrics for benchmarking purposes. The implemented library offers an autonomous tool for evaluating any decision problem. The presented library is an important addition to decision support systems based on MCDA methods as it provides additional possibilities for analysis of scenarios’ reliability

Prioritizing lean techniques by employing Multi-Criteria Decision-Making (MCDM): The case of MCoutinho

The business cycle in the automotive industry follows the general economic cycle closely and therefore, undergoes cyclical fluctuations over time. Companies in the sector are faced with challenges and need to deal with market demands efficiently and quickly to stay competitive. Lean approach is one of the strategies that can aid firms to improve their competitiveness by minimizing waste (Pullan et al., 2013). In order to benefit from a lean approach, the first step is to select a proper tool based on the available resources and requirements of the company. Due to the fact that numerous lean tools have been introduced over time, decision makers in company may encounter challenges in selecting the proper one with regard to their demands. To deal with such an issue, Multi-Criteria Decision-Making (MCDM) can greatly assist decision makers to compare available alternatives and consequently select the best possible solution among them. This study aims at improving the operational process in MCoutinho Group, a Portuguese well-known company in the automotive sector, by helping the management board in selecting lean tool due to the company preferences. In this study, the applicability (and results) of the application of some MCDM techniques (SAW, TOPSIS, and VIKOR) is examined to compare ten lean tools, determined based on the literature. The results reveal some gaps between company requirements and the demands which have been considered in previous surveys. The process applied can save the costs of trial and error of implementing different lean tools. And finally, adopting such a lean tool that has been selected totally based on the exclusive requirements of the company can improve efficiency in the company.O ciclo de negócios na indústria automotiva segue de perto o ciclo econômico geral e, portanto, sofre flutuações cíclicas ao longo do tempo. As empresas do setor enfrentam desafios e precisam lidar com as demandas do mercado de forma eficiente e rápida para se manterem competitivas. A abordagem enxuta é uma das estratégias que pode ajudar as empresas a melhorar sua competitividade, minimizando o desperdício (Pullan et al., 2013). Para se beneficiar de uma abordagem enxuta, o primeiro passo é selecionar uma ferramenta adequada com base nos recursos disponíveis e requisitos da empresa. Devido ao fato de que várias ferramentas enxutas foram introduzidas ao longo do tempo, os tomadores de decisão na empresa podem encontrar desafios ao selecionar a ferramenta adequada com relação às suas demandas. Para lidar com essa questão, a Tomada de Decisão Multi-Critérios (MCDM) pode ajudar muito os tomadores de decisão a comparar as alternativas disponíveis e, conseqüentemente, selecionar a melhor solução possível entre elas. Este estudo tem como objetivo melhorar o processo operacional do Grupo MCoutinho, empresa portuguesa de renome no setor automóvel, auxiliando a administração na seleção da ferramenta enxuta em função das preferências da empresa. Neste estudo, a aplicabilidade (e resultados) da aplicação de algumas técnicas MCDM (SAW, TOPSIS e VIKOR) é examinada para comparar dez ferramentas enxutas, determinadas com base na literatura. Os resultados revelam algumas lacunas entre os requisitos da empresa e as demandas consideradas em pesquisas anteriores. O processo aplicado pode economizar os custos de tentativa e erro de implementação de diferentes ferramentas enxutas. E, por fim, a adoção de uma ferramenta tão enxuta que foi selecionada totalmente com base nos requisitos exclusivos da empresa pode melhorar a eficiência da empresa

A systematic simulation-based multi-criteria decision-making approach for the evaluation of semi-fully flexible machine system process parameters

Current manufacturing system health management is of prime importance due to the emergence of recent cost-effective and -efficient prognostics and diagnostics capabilities. This paper investigates the most used performance measures viz. Throughput Rate, Throughput Time, System Use, Availability, Average Stay Time, and Maximum Stay Time as alternatives that are responsible for the diagnostics of manufacturing systems during real-time disruptions. We have considered four different configurations as criteria on which to test with the proposed integrated MCDM (Multi-Criteria Decision-Making)-TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution)-based simulation approach. The main objective of this proposed model is to improve the performance of semi–fully flexible systems and to maximize the production rate by ranking the parameters from most influenced to least. In this study, first, the performance of the considered process parameters are analyzed using a simulation approach, and furthermore the obtained results are validated using real-time experimental results. Thereafter, using an Entropy method, the weights of each parameter are identified and then the MCDM-based TOPSIS is applied to rank the parameters. The results show that Throughput tTme is the most affected parameter and that Availability, average stay time, and max stay time are least affected in the case of no breakdown of machine condition. Similarly, Throughput Time is the most affected parameter and Maximum Stay Time is the least affected parameter in the case of the breakdown of machine condition. Finally, the rankings from the TOPSIS method are compared with the PROMETHEE method rankings. The results demonstrate the ability to understand system behavior in both normal and uncertain conditions.This work has been, also, supported by the FCT within the RD Units Project Scope: UIDP/04077/2020 and UIDB/04077/2020

AN EVALUATION OF ALTERNATİVE METHODS FOR FINANCIAL PERFORMANCE: EVIDENCE FROM TURKEY (ISTANBUL STOCK EXCHANGE)

This study aims to determine which financial performance ranking methods accurately predict the actual rankings by using multiple criteria decision techniques, and it compares the accuracy of the rankings based on the financial performance indicators and the market based approach which involves market value and average return. Companies listed in BIST50 index (Borsa Istanbul) were investigated, as a result, when considering average return, Promethee and Copras produced similar and consistent rankings. Besides, since it places emphasize on the functional structures of variables, Promethee method was noted to produce the most accurate rankings, thus deemed most effective method helping investors give rational decisions

The Application of WSM, WPM and WASPAS Multicriteria Methods for Optimum Operating Conditions Selection in Machining Operations

Optimal condition selection in machining operations is an imperative decision for the process engineer as it influences improved tool life and surface roughness values. As the aluminium market is extremely competitive, process engineers strive to understand what to do to gain preference from prospective customers. From this viewpoint, the criteria responsible for operating decisions should be examined. In this paper the WSM, WPM and WASPAS multicriteria methods are proposed for optimal machining conditions for turned aluminium bars. A stepwise methodology of the WSM, WPM and WASPAS methods is detailed. The proposed technique was tested on published data regarding the turning of an aluminium bar, machined on a lathe machine. The case study consists of three input parameters (spindle speed, feed rate and depth of cut) and four responses (cutting temperature, cutting force, surface roughness and material removal rate). After analysing the experimental data using the models, the entropy method chose material removal rate was chosen as the best. Using the three other models, the best selection was run 17 which correspond to an input parameter of 605 rpm spindle speed, 0.12 mm/rev feed rate and 1.8 mm depth of cut. This article offers a completely new approach to operating condition selection in the turning of the aluminium bar. In the current aluminium market, it is extremely important to understand the operating conditions of the machine for enlarged customer patronage and sustainability. The unique feature of this approach is the elevated level of reliability it exhibits