A New Entropy Measurement for the Analysis of Uncertain Data in MCDA Problems Using Intuitionistic Fuzzy Sets and COPRAS Method

In this paper, we propose a new intuitionistic entropy measurement for multi-criteria decision-making (MCDM) problems. The entropy of an intuitionistic fuzzy set (IFS) measures uncertainty related to the data modelling as IFS. The entropy of fuzzy sets is widely used in decision support methods, where dealing with uncertain data grows in importance. The Complex Proportional Assessment (COPRAS) method identifies the preferences and ranking of decisional variants. It also allows for a more comprehensive analysis of complex decision-making problems, where many opposite criteria are observed. This approach allows us to minimize cost and maximize profit in the finally chosen decision (alternative). This paper presents a new entropy measurement for fuzzy intuitionistic sets and an application example using the IFS COPRAS method. The new entropy method was used in the decision-making process to calculate the objective weights. In addition, other entropy methods determining objective weights were also compared with the proposed approach. The presented results allow us to conclude that the new entropy measure can be applied to decision problems in uncertain data environments since the proposed entropy measure is stable and unambiguous.

Development of a Flame Shield for use in Domestic Gas Stoves

Gas stove is one of the most common and basic domestic appliances found in any home in the subcontinent. It is the foremost article used for cooking at home, and thus necessitates interaction with it by the users in a significant way. Despite the advent of more advanced devices like the microwave oven or the induction cooktop, a traditional gas stove reigns supreme in the lives of homemakers. Therefore, an endeavor was undertaken to design a product that would improve the usage and performance of a gas stove, by way of alleviating the general problems faced by users in its operation. Design thinking strategies had been followed throughout the stages of the product development, beginning with a customer survey to understand the desirable needs, followed by translating them into tangible target specifications for the product to achieve, and finally using the ideation techniques to develop the concepts into feasible product. The morphological method of concept generation yielded possible concepts aimed towards a solution, which were evaluated by following the analysis techniques of Forced Decision (FD) and Decision Alternative Ratio Evaluation (DARE). The filtered concept was then subjected to product architecture design, where it was given an efficient physical form by using the Computer Aided Design (CAD) software SolidWorks, and lastly, the parametric design result was evaluated by means of various Design For Excellence (DFX) guidelines. The product turned out to be an appendage to the existing stove, that would shield the flame and provide efficient operation along with enhanced safety and ease of use, as validated by DFX principles and a Computational Fluid Dynamics (CFD) study to gauge its performance in relation to that of a standalone gas stove. This paper comprises of expositions of all the aforementioned processes as carried out, along with the final result, and pertinent analyses.

Supplier Selection Risk: A New Computer-Based Decision-Making System with Fuzzy Extended AHP

Supplier risks have attracted significant attention in the supply chain risk management literature. In this article, we propose a new computational system based on the ‘Fuzzy Extended Analytic Hierarchy Process (FEAHP)’ method for supplier selection while considering the relevant risks. We sought to evaluate the opportunities and limitations of using the FEAHP method in supplier selection and analyzed the support of the system developed through the real case of a Brazilian oil and natural gas company. The computational approach based on FEAHP automates supplier selection by determining a hierarchy of criteria, sub-criteria, and alternatives. First, the criteria and sub-criteria specific to the selection problem were identified by the experts taking the relevant literature as a starting point. Next, the experts performed a pair-wise comparison of the predefined requirements using a linguistic scale. This evaluation was then quantified by calculating the priority weights of criteria, sub-criteria, and alternatives. The best decision alternative is the one with the highest final score. Sensitivity analysis was performed to verify the results of the proposed model. The FEAHP computer approach automated the supplier selection process in a rational, flexible, and agile way, as perceived by the focal company. From this, we hypothesized that using this system can provide helpful insights in choosing the best suppliers in an environment of risk and uncertainty, thereby maximizing supply chain performance.

Quantum Cognitive Triad: Semantic Geometry of Context Representation

The paper describes an algorithm for semantic representation of behavioral contexts relative to a dichotomic decision alternative. The contexts are represented as quantum qubit states in two-dimensional Hilbert space visualized as points on the Bloch sphere. The azimuthal coordinate of this sphere functions as a one-dimensional semantic space in which the contexts are accommodated according to their subjective relevance to the considered uncertainty. The contexts are processed in triples defined by knowledge of a subject about a binary situational factor. The obtained triads of context representations function as stable cognitive structure at the same time allowing a subject to model probabilistically-variative behavior. The developed algorithm illustrates an approach for quantitative subjectively-semantic modeling of behavior based on conceptual and mathematical apparatus of quantum theory.

Lexicographic Decision Rule

The lexicographic decision rule is one of the simplest methods of choosing among decision alternatives. It is based on a simple priority ranking of the attributes available. According to the lexicographic decision rule, a decision alternative is better than another alternative if and only if it is better than the other alternative in the most important attribute on which the two alternatives differ. In other words, the lexicographic decision rule does not allow trade-offs among the various attributes. For example, if quality is considered to be more important than cost, no difference in price can compensate for a difference in quality: The lexicographic decision rule chooses the item with the best quality regardless of the cost. Over the years, the lexicographic decision rule has been compared to various statistical learning methods, including multiple linear regression, support vector machines, decision trees, and random forests. The results show that the lexicographic decision rule can sometimes compete remarkably well with more complex statistical methods, and even outperform them, despite its naively simple structure. These results have stimulated a rich scientific literature on why, and under what conditions, lexicographic decision rules yield accurate decisions. Due to the simplicity of its decision process, its fast execution time, and the robustness of its performance in various decision environments, the lexicographic decision rule is considered to be a plausible model of human decision making. In particular, the lexicographic decision rule is put forward as a model of how the human mind implements bounded rationality to make accurate decisions when information is scarce, time is short, and computational capacity is limited.

Public Health Interventions with Harms and Benefits: A Graphical Framework for Evaluating Tradeoffs

Background Evaluations of public health interventions typically report benefits and harms aggregated over the population. However, benefits and harms are not always evenly distributed. Examining disaggregated outcomes enables decision makers to consider health benefits and harms accruing to both intended intervention recipients and others in the population. Methods We provide a graphical framework for categorizing and comparing public health interventions that examines the distribution of benefit and harm between and within population subgroups for a single intervention and compares distributions of harm and benefit for multiple interventions. We demonstrate the framework through a case study of a hypothetical increase in the price of meat (5%, 10%, 25%, or 50%) that, via elasticity of demand, reduces consumption and consequently reduces body mass index. We examine how inequalities in benefits and harms (measured by quality-adjusted life-years) are distributed across a population of white and black males and females. Results A 50% meat price increase would yield the greatest net benefit to the population. However, because of reduced consumption among low-weight individuals, black males would bear disproportionate harm relative to the benefit they receive. With increasing meat price, the distribution of harm relative to benefit becomes less “internal” to those receiving benefit and more “distributed” to those not receiving commensurate benefit. When we segment the population by sex only, this result does not hold. Conclusions Disaggregating harms and benefits to understand their differential impact on subgroups can strongly affect which decision alternative is deemed optimal, as can the approach to segmenting the population. Our framework provides a useful tool for illuminating key tradeoffs relevant to harm-averse decision makers and those concerned with both equity and efficiency.

APPLICATION OF AHP FOR SUPPLIER SELECTION IN CONSTRUCTION COMPANIES

The procurement process is an important process in supply chain management as it is the spearhead of the entire process. In carrying out the procurement process, there are often problems with the supplier selection activities. This is because the supplier selection process spends a lot of time and resources collecting data and conducting careful analysis that will affect the entire decision alternative. In making decisions relating to the many criteria and the number of alternative suppliers, it requires an effective and uncomplex assessment technique, but it provides accurate results. A mapping and determination of supplier selection criteria is required as a basis for valuation to obtain a qualified supplier. This study focused on PT. XYZ is a construction company in South Tangerang. Analytical Hierarchy Process (AHP) is used to determine the best supplier, there are 4 variables that are reference in conducting the selection of suppliers, such as: cost, quality, delivery, and service. The result in the selection of the supplier company is cost with a weight of 0.268, quality with a weight of 0.290, delivery with a weighting of 0.248, and the service with a weight of 0.194 where conclusions obtained from the analysis of the selection of the best suppliers and in accordance with the criteria, namely PT. CBL for iron suppliers, PT.SAS for cement suppliers, and PT. Citra BSD for suppliers of natural materials

A First Example: Forager Patch Selection

This chapter illustrates how to use state- and prediction-based theory (SPT) by applying it to an extremely simple model of how hypothetical foragers select among patches that differ in both food availability and predation risk. This example uses two common techniques of SPT. First, individuals predict conditions using the simplest approach that lets them adapt to changing conditions: by simply assuming that current conditions will persist until the time horizon. The second typical SPT technique is to simplify evaluation of the fitness measure for a particular decision alternative by assuming that the individual will use the alternative until the time horizon. The chapter then evaluates the quality of decisions made via SPT. It also shows how SPT allows one to make models less simple and more realistic and capable.

Quantum Cognitive Triad. Semantic Geometry of Context Representation

The paper describes an algorithm for cognitive representation of triples of related behavioral contexts two of which correspond to mutually exclusive states of some binary situational factor while uncertainty of this factor is the third context. The contexts are mapped to vector states in the two-dimensional quantum Hilbert space describing a dichotomic decision alternative in relation to which the contexts are subjectively recognized. The obtained triad of quantum cognitive representations functions as a minimal carrier of semantic relations between the contexts, which are quantified by phase relations between the corresponding quantum representation states. The described quantum model of subjective semantics supports interpretable vector calculus which is geometrically visualized in the Bloch sphere view of quantum cognitive states.

Social-Media based DSM for Strategic Decision Making: Corruption Case

Social-media is a communication media based on internet technology. It is a big virtual place where data and information could be practically mined. Furthermore, the data and information are able to be operated in research purposes. One of them, they could be mined to generate decision parameters. This study operated social media to dig all clues in topic corruption. They then generated to become decision parameters that are ready to be involved in to the model. Decision support model (DSM) was constructed scientifically based on two main methods; fuzzy logic and mathematical model. They were functioned respectively to eliminate a bias characteristic of parameters value and calculate the quality of corruption handling and propose the most objective strategic decision to solve the problem, particularly in Indonesia. The model was able to simulate the decision alternative measurement and propose the best decision of several strategic decision alternatives.