The weighted average multiexperton

Linares‐Mustarós, Salvador; Comalat, Joan Carles Ferrer i; Corominas-Coll, Dolors; Merigó, José M.

doi:10.1016/j.ins.2020.08.029

Cited by 5 publications

(7 citation statements)

References 39 publications

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“…where A and B are the values in (15). With these hypotheses, since 0 ≤ c ≤ 1, we see that a convergent trajectory of income is always obtained.…”

Section: Fuzzy Dynamic Model For Stationary Growthmentioning

confidence: 67%

“…In this certain case, using (15), we have the next trajectory for the income Y t = 2533.33 − 1533.33•(0.85) t t = 0, 1, 2, 3, . .…”

Section: Example 1-crisp Casementioning

confidence: 99%

“…However, this means taking an uncertain magnitude as definite in the models, resulting in a loss of information due to all possible cases not being processed. Thanks to the theory of possibility [11], fuzzy sets theory [12] offers a new way of preserving the inaccuracy of economic phenomena [13][14][15]. By assigning a possibility distribution to a magnitude that is not known with certainty, it is possible to obtain a better adaptation to economic reality [16][17][18] since the obtained prediction contemplates and provides more information, given that it will take all information into account when applying the model to ultimately provide possible values for the resulting variables, with a degree of possibility for each.…”

Section: Introductionmentioning

confidence: 99%

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A Fuzzy Economic Dynamic Model

2021

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In the study presented here, fuzzy logic was used to analyze the behavior of a model of economic dynamics that assumes income to be in equilibrium when it is composed of consumption and investment, that is, when savings and investment are equal. The study considered that consumption and savings depend on the income of the previous period through uncertain factors, and, at the same time, that investment is an uncertain magnitude across various periods, represented as a fuzzy number with a known membership function. Under these conditions, the model determines the factor of income growth and investments required to maintain equilibrium, as well as the uncertain values of income for the different periods, expressed through fuzzy numbers. The study also analyzes the conditions for their convergence and the fuzzy value that income represents in equilibrium.

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“…where A and B are the values in (15). With these hypotheses, since 0 ≤ c ≤ 1, we see that a convergent trajectory of income is always obtained.…”

Section: Fuzzy Dynamic Model For Stationary Growthmentioning

confidence: 67%

“…In this certain case, using (15), we have the next trajectory for the income Y t = 2533.33 − 1533.33•(0.85) t t = 0, 1, 2, 3, . .…”

Section: Example 1-crisp Casementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Fuzzy Economic Dynamic Model

2021

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“…The idea of considering the future in a pessimistic, optimistic and highly plausible scenario is the basis of these types of numbers that collect all values with some degree of possibility greater than zero. It is the ease of use of these mathematical structures [4][5][6][7] that allows uncertainty to be incorporated efficiently into any economic model regarding the behavior of economic, social and financial scenarios. This is especially necessary when sudden changes in the values of the variables are expected due to events not reflected in the historical series.…”

Section: Introductionmentioning

confidence: 99%

Incorporating Fuzzy Logic in Harrod’s Economic Growth Model

2021

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This paper suggests the possibility of incorporating the methodology of fuzzy logic theory into Harrod’s economic growth model, a classic model of economic dynamics for studying the growth of a developing economy based on the assumption that an economy with only savings and investment income is in equilibrium when savings are equal to investment. This model was the first precursor to exogenous growth models, which in turn gave rise to endogenous growth models. This article therefore represents a first step towards introducing fuzzy logic into economic growth models. The study concerned considers consumption and savings to depend on income by means of uncertain factors, and investment to depend on the variation of income through the accelerator factor, which we consider uncertain. These conditions are used to determine the equilibrium growth rate of income and investment, as well as the uncertain values for these variables in terms of fuzzy numbers. As a result, the new model is shown to expand the classical model by incorporating uncertainty into its variables.

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“…We can use the concept of distance to calculate the deviation between real data and predicted data. After conducting a thorough bibliographic review, we observed that the concept of distance is the one most used by different researchers [8][9][10][11][12]. When we work with the concept of distance, it is advisable to add them using an aggregation operator where we will work on the information giving different degrees of importance to each of the elements [13].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Branch-and-Bound Algorithm with OWA Operators in the Case of Consumer Decision Making

et al. 2021

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The ordered weighted averaging (OWA) operator is one of the most used techniques in the operator’s aggregation procedure. This paper proposes a new assignment algorithm by using the OWA operator and different extensions of it in the Branch-and-bound algorithm. The process is based on the use of the ordered weighted average distance operator (OWAD) and the induced OWAD operator (IOWAD). We present it as the Branch-and-bound algorithm with the OWAD operator (BBAOWAD) and the Branch-and-bound algorithm with the IOWAD operator (BBAIOWAD). The main advantage of this approach is that we can obtain more detailed information by obtaining a parameterized family of aggregation operators. The application of the new algorithm is developed in a consumer decision-making model in the city of Barcelona regarding the selection of groceries by districts that best suit their needs. We rely on the opinion of local commerce experts in the city. The key advantage of this approach is that we can consider different sources of information independent of each other.

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The weighted average multiexperton

Cited by 5 publications

References 39 publications

A Fuzzy Economic Dynamic Model

A Fuzzy Economic Dynamic Model

Incorporating Fuzzy Logic in Harrod’s Economic Growth Model

Fuzzy Branch-and-Bound Algorithm with OWA Operators in the Case of Consumer Decision Making

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