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Statistical inference on uncertain nonparametric regression model Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2021-02-17 Jianhua Ding, Zhiqiang Zhang
Nonparametric regression analysis is a useful method to explore the relationships among the variables when a parametric form is not known. Assuming the observations of the model are imprecise and modeling the observed data via uncertain variables, this paper proposes least squares estimation of uncertain nonparametric regression model to explore the functional relationships between response variable
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A structured solution framework for fuzzy minimum spanning tree problem and its variants under different criteria Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2021-02-15 Ke Wang, Yulin Zhou, Guichao Tian, Mark Goh
This paper develops a unified and structured solution framework for the minimum spanning tree (MST) problem and its variants (e.g., constrained MST problem and inverse MST problem) on networks with fuzzy link weights. It is applicable to any additive decision criterion under fuzziness (e.g., expected value, value at risk, and conditional value at risk), for generalized cases that the link weights may
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Two-person cooperative uncertain differential game with transferable payoffs Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2021-02-13 Yi Zhang, Jinwu Gao, Xiang Li, Xiangfeng Yang
Uncertain differential game models conflicts and interests among players in the context of an uncertain dynamic system. However, cooperative behavior in uncertain differential game is an unexplored terrain. This paper proposes a spectrum of a cooperative uncertain differential game with transferrable payoffs. First, group rationality is achieved by maximizing the coalitional payoff through an uncertain
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An inverse prospect theory-based algorithm in extended incomplete additive probabilistic linguistic preference relation environment and its application in financial products selection Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-11-05 Nana Liu, Zeshui Xu, Yue He, Xiao-Jun Zeng
Selecting financial products is one of the most fundamental investment activities to both individuals and companies, and therefore it is very important to establish an efficient and practical method for financial products selection. To address the challenge of the complicated decision-making environment and decision makers’ expression habits for the selection of financial products, this paper develops
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A novel approach to relative importance ratings of customer requirements in QFD based on probabilistic linguistic preferences Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-10-26 Yinfeng Du, Dun Liu
Quality function deployment (QFD) is a customer-oriented product/service design tool with diversified team members reaching a consensus in developing a new or an improved product/service to maximize customer satisfaction. Determining the relative importance ratings (RIRs) of customer requirements (CRs) is actually a multiple attribute decision making (MADM) problem, which is regarded as an essential
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Evidential evolving C-means clustering method based on artificial bee colony algorithm with variable strings and interactive evaluation mode Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-10-06 Zhi-gang Su, Hong-yu Zhou, Yong-sheng Hao
The Evidential C-Means algorithm provides a global treatment of ambiguity and uncertainty in memberships when partitioning attribute data, but still requires the number of clusters to be fixed as a priori, like most existing clustering methods do. However, the users usually do not know the exact number of clusters in advance, particularly in practical engineering. To relax this requirement, this paper
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Minimax models for capacitated p -center problem in uncertain environment Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-10-02 Bo Zhang, Jin Peng, Shengguo Li
The capacitated p-center problem is concerned with how to select p locations for facility centers and assign demand points to them such that the maximum distance between a demand point and its nearest center is minimized. This paper focuses on the capacitated p-center problem in an uncertain environment, in which demands and distances are regarded as uncertain variables. Consequently, two minimax models
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Optimal control for uncertain discrete-time singular systems under expected value criterion Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-10-02 Yadong Shu, Bo Li, Yuanguo Zhu
Optimal control problems governed by two different types of uncertain discrete-time singular systems are investigated under expected value criterion. The objective function including uncertain variables is optimized with the help of expected value method provided that the singular systems are both regular and impulse-free. At first, based on the principle of dynamic programming, a recurrence equation
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Portfolio management with background risk under uncertain mean-variance utility Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-09-30 Xiaoxia Huang, Guowei Jiang
This paper studies comparative static effects in a portfolio selection problem when the investor has mean-variance preferences. Since the security market is complex, there exists the situation where security returns are given by experts’ estimates when they cannot be reflected by historical data. This paper discusses the problem in such a situation. Based on uncertainty theory, the paper first establishes
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Uncertain SEIAR model for COVID-19 cases in China Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-09-24 Lifen Jia, Wei Chen
The Susceptible-Exposed-Infectious-Asymptomatic-Removed (SEIAR) epidemic model is one of most frequently used epidemic models. As an application of uncertain differential equations to epidemiology, an uncertain SEIAR model is derived which considers the human uncertainty factors during the spread of an epidemic. The parameters in the uncertain epidemic model are estimated with the numbers of COVID-19
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Uncertain growth model for the cumulative number of COVID-19 infections in China Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-09-19 Zhe Liu
As a type of coronavirus, COVID-19 has quickly spread around the majority of countries worldwide, and seriously threatens human health and security. This paper aims to depict cumulative numbers of COVID-19 infections in China using the growth model chosen by cross validation. The residual plot does not look like a null plot, so we can not find a distribution function for the disturbance term that is
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Numerical solution and parameter estimation for uncertain SIR model with application to COVID-19 Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-09-17 Xiaowei Chen, Jing Li, Chen Xiao, Peilin Yang
Developing algorithms for solving high-dimensional uncertain differential equations has been an exceedingly difficult task. This paper presents an \(\alpha \)-path-based approach that can handle the proposed high-dimensional uncertain SIR model. We apply the \(\alpha \)-path-based approach to calculating the uncertainty distributions and related expected values of the solutions. Furthermore, we employ
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A relation between moments of Liu process and Bernoulli numbers Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-09-16 Guanzhong Ma, Xiangfeng Yang, Xiao Yao
This paper finds a relation between moments of Liu process and Bernoulli numbers. Firstly, by an exponential generating function of Bernoulli numbers, a useful integral formula is obtained. Secondly, based on this integral formula, the moments of a normal uncertain variable and Liu process are expressed via Bernoulli numbers.
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Analysis and prediction of confirmed COVID-19 cases in China with uncertain time series Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-09-16 Tingqing Ye, Xiangfeng Yang
This paper presents an uncertain time series model to analyse and predict the evolution of confirmed COVID-19 cases in China, excluding imported cases. Compared with the results of the classical time series model, the uncertain time series model could better describe the COVID-19 epidemic by using an uncertain hypothesis test to filter out outliers. This improvement is reflected in the two observations
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Initial value estimation of uncertain differential equations and zero-day of COVID-19 spread in China Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-09-15 Waichon Lio, Baoding Liu
Assume an uncertain process follows an uncertain differential equation, and some realizations of this process are observed. Parameter estimation for the uncertain differential equation that fits the observed data as much as possible is a core problem in practice. This paper first presents a problem of initial value estimation for uncertain differential equations and proposes an estimation method. In
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Towards fuzzy anomaly detection-based security: a comprehensive review Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-07-23 Mohammad Masdari, Hemn Khezri
In the data security context, anomaly detection is a branch of intrusion detection that can detect emerging intrusions and security attacks. A number of anomaly detection systems (ADSs) have been proposed in the literature that using various algorithms and techniques try to detect the intrusions and anomalies. This paper focuses on the ADS schemes which have applied fuzzy logic in combination with
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Stability analysis for uncertain differential equation by Lyapunov’s second method Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-07-21 Zhiyong Huang, Chunliu Zhu, Jinwu Gao
Uncertain differential equation is a type of differential equation driven by Liu process that is the counterpart of Wiener process in the framework of uncertainty theory. The stability theory is of particular interest among the properties of the solutions to uncertain differential equations. In this paper, we introduce the Lyapunov’s second method to study stability in measure and asymptotic stability
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Probabilistic-based expressions in behavioral multi-attribute decision making considering pre-evaluation Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-07-20 Zhenzhen Ma, Jianjun Zhu, Shitao Zhang
A behavioral multi-attribute decision making (BMADM) problem with probabilistic-based expressions is studied by considering decision-maker’s (DM) risk attitude and pre-evaluation. With consideration of information expressions for uncertainty, probabilistic interval numbers (PINs) and probabilistic linguistic terms (PLTs) are utilized to depict pre-evaluation information with respect to quantitative
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Managing consensus reaching process with self-confident double hierarchy linguistic preference relations in group decision making Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-07-18 Xunjie Gou, Zeshui Xu, Xinxin Wang, Huchang Liao
Group decision making (GDM) can be defined as an environment where there exist a set of possible alternatives and a set of individuals (experts, judgements, etc.). Preference relation is one of the most widely used preference representation structures in GDM. Considering that the self-confidence degree is an important part to express preference information, and double hierarchy linguistic preference
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Barrier option pricing formulas of an uncertain stock model Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-07-18 Kai Yao, Zhongfeng Qin
As applications of the uncertainty theory to finance, uncertain stock models have been presented to describe the prices of stocks strongly influenced by human uncertainty. So far, large progress has been achieved on pricing problems of path-independent options of the uncertain stock models. This paper investigates a type of path-dependent exotic options of an uncertain stock model which are named barrier
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A random intuitionistic fuzzy factor analysis model for complex multi-attribute large group decision-making in dynamic environments Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-07-17 Xiaohong Chen, Mengjing Wu, Chunqiao Tan, Tao Zhang
The challenge of complex multi-attribute large group decision-making (CMALGDM) is reflected from three perspectives: interrelated attributes, large group decision makers (DMs) and dynamic decision environments. However, there are few decision techniques that can address the three perspectives simultaneously. This paper proposes a random intuitionistic fuzzy factor analysis model, aiming to address
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A group decision making with probability linguistic preference relations based on nonlinear optimization model and fuzzy cooperative games Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-06-16 Pei Liang, Junhua Hu, Bo Li, Yongmei Liu, Xiaohong Chen
The aim of the paper is to solve the group decision making problems which contain inconsistent probabilistic linguistic preference relations (PLPRs) and unknown expert weights. When the PLPRs are inconsistent, there are contradictories in the preference relations expressed by the experts. The evaluation value with contradictory information will bring out an incorrect consequence in decision making
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Probabilistic linguistic multi-criteria decision-making based on double information under imperfect conditions Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-06-09 Na Yue, Dongrui Wu, Jialiang Xie, Shuili Chen
In this paper, we study four projection-based normalization models and a decision-making method for probabilistic linguistic multi-criteria decision-making problems, in which the assessment information about an alternative with respect to a criterion is incomplete and the criteria weight values are not precisely known but the ranges are available. To apply the projection to the probabilistic linguistic
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Web celebrity shop assessment and improvement based on online review with probabilistic linguistic term sets by using sentiment analysis and fuzzy cognitive map Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-06-08 Decui Liang, Zhuoyin Dai, Mingwei Wang, Jinjun Li
As a representative of the new economy, the web celebrity economy has achieved significant development in China with the rapid development of information technology and the Internet. In this environment, web celebrity shops encounter fierce business competition of peer competitors. Online reviews which imply the consumers’ attitudes and sentiments give the web celebrity shops good feedback to improve
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On consistency and priority weights for interval probabilistic linguistic preference relations Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-06-04 Xiangqian Feng, Xiaodong Pang, Lan Zhang
When expressing preferences with different probability weights for different linguistic terms, only partial assessment information is usually to be provided. Then the probability information can be normalized to the interval probability, hence, using interval probabilistic linguistic term sets (IPLTs) is more appropriate. Considering this situation, interval probabilistic linguistic preference relation
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Factor relation analysis for sustainable recycling partner evaluation using probabilistic linguistic DEMATEL Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-05-21 Peng Li, Ju Liu, Cuiping Wei
Evaluating and selecting suitable sustainable recycling partners is a key work in sustainable supply chain management. In order to deal with the probabilistic linguistic influence relations between criteria and obtain the key factors that influence the evaluation results of sustainable recycling partners, we propose a new decision-making trial and evaluation laboratory (DEMATEL) method. First, we propose
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Multi-criteria sorting decision making based on dominance and opposition relations with probabilistic linguistic information Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-05-20 Hong-gang Peng, Jian-qiang Wang
The probabilistic linguistic term set (PLTS) is a powerful tool for describing linguistic evaluations derived from expert teams and has adequate capability to identify preferences among different evaluations. Due to the practicability of PLTSs, probabilistic linguistic decision making problems have been widely investigated in recent years. However, no study on probabilistic linguistic outranking relations
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A new parallel fuzzy data envelopment analysis model for parallel systems with two components based on Stackelberg game theory Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-04-25 Xiao Shi; Ali Emrouznejad; Minyue Jin; Feng Yang
This paper investigates the problem of efficiency measurement for parallel systems with two components based on Stackelberg game theory, while some inputs/outputs are fuzzy numbers. Conventional DEA models treat DMUs as “Black Boxes”. While in this paper, we propose a new parallel fuzzy DEA model to calculate the efficiency scores for each DMU’s whole system and its sub-systems. Through the Stackelberg
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A direct consistency test and improvement method for the analytic hierarchy process Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-04-07 Kang Xu; Jiuping Xu
The consistency test is a vital component of pairwise comparison matrices if meaningful results are to be guaranteed, and it has been studied extensively since the analytic hierarchy process was developed by Saaty. However, when using the existing methods, it is imperative to carry out matrix operations, which are usually not intuitional. In this paper, a direct method, from the perspective of 3 tuples
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Robust parallel-batching scheduling with fuzzy deteriorating processing time and variable delivery time in smart manufacturing Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-04-03 Shaojun Lu; Jun Pei; Xinbao Liu; Panos M. Pardalos
Smart manufacturing is an effective way to improve the efficiency of resource utilization and reduce the response time of making joint decisions for the enterprises. Though, with the globalization of manufacturing enterprises, manufacturing optimization problems often occur in complex manufacturing systems under the deteriorating and fuzzy environment, which brings many challenges to smart manufacturing
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Dynamic variational inequality in fuzzy environments Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-04-02 Xing Wang; Zeng-bao Wu; Yi-bin Xiao; Kok Lay Teo
This paper introduces a class of differential fuzzy variational inequalities, the model provides an efficient approach for solving many dynamic multi-objective optimization problems in fuzzy environments. An existence theorem of the Carathéodory weak solution for the model is established under some suitable assumptions. An algorithm, supported by the convergence analysis, is developed to find the solution
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A fuzzy evaluation approach with the quasi-ordered set: evaluating the efficiency of decision making units Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-04-02 Xiao-Li Meng; Liu-Tang Gong; Jen-Chih Yao
This work proposes an inequality approach with the quasi-ordered set to evaluate the performances of decision making units (DMUs). In real world applications, input and output data are often imprecise and fluctuated. In this case, a fuzzy inequality approach is proposed to evaluate DMUs with fuzzy data. Fuzzy inequalities consist of fuzzy expressions of the production possibility set and the line segment
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A novel plausible reasoning based on intuitionistic fuzzy propositional logic and its application in decision making Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-04-02 Xinxin Wang; Zeshui Xu; Xunjie Gou
Automatic reasoning based on propositional logic is considered as an important tool in machine learning, and intuitionistic fuzzy sets have turned out to deal with vague and uncertain information effectively in real world. In this paper, a novel plausible reasoning based on intuitionistic fuzzy propositional logic is proposed. On the basis of it, the categories of intuitionistic fuzzy logic proposition
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Mathematical programming approach to formulate intuitionistic fuzzy regression model based on least absolute deviations Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-02-17 Liang-Hsuan Chen; Sheng-Hsing Nien
Fuzzy regression models are widely used to investigate the relationship between explanatory and response variables for many decision-making applications in fuzzy environments. To include more fuzzy information in observations, this study uses intuitionistic fuzzy numbers (IFNs) to characterize the explanatory and response variables in formulating intuitionistic fuzzy regression (IFR) models. Different
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Option implied moments obtained through fuzzy regression Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-02-12 Silvia Muzzioli; Luca Gambarelli; Bernard De Baets
The aim of this paper is to investigate the potential of fuzzy regression methods for computing more reliable estimates of higher-order moments of the risk-neutral distribution. We improve upon the formula of Bakshi et al. (RFS 16(1):101–143, 2003), which is used for the computation of market volatility and skewness indices (such as the VIX and the SKEW indices traded on the Chicago Board Options Exchange)
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Harmonizing two approaches to fuzzy random variables Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-02-11 Miriam Alonso de la Fuente; Pedro Terán
We prove a measurability result which implies that the measurable events concerning the values of a fuzzy random variable, in two related mathematical approaches wherein the codomains of the variables are different spaces, are the same (provided both approaches apply). Further results on the perfectness of probability distributions of fuzzy random variables are presented.
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A scalarization method for fuzzy set optimization problems Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-02-10 Masamichi Kon
In the present paper, we consider fuzzy optimization problems which involve fuzzy sets only in the objective mappings, and give two concepts of optimal solutions which are non-dominated solutions and weak non-dominated solutions based on orderings of fuzzy sets. First, by using level sets of fuzzy sets, the fuzzy optimization problems treated in this paper are reduced to set optimization problems,
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On weak consistency of interval additive reciprocal matrices Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-02-08 Fang Liu; Jia-Wei Zhang; Qin Yu; Ya-Nan Peng; Witold Pedrycz
When one estimates the importance of alternatives under rational choice, it is natural to avoid self-contradiction from the viewpoint of psychology. Due to the vagueness encountered in a manner analogous to human thought, decision makers always exhibit limited rationality. The judgements could be expressed as interval-valued comparison matrices within the framework of analytic hierarchy process. In
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Finite-time stability of uncertain fractional difference equations Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2020-02-07 Qinyun Lu; Yuanguo Zhu
Uncertain fractional difference equations may preferably describe the behavior of the systems with the memory effect and discrete feature in the uncertain environment. So it is of great significance to investigate their stability. In this paper, the concept of finite-time stability almost surely for uncertain fractional difference equations is introduced. A finite-time stability theorem is then stated
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A survey of decision-making methods with probabilistic linguistic information: bibliometrics, preliminaries, methodologies, applications and future directions Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2019-10-24 Huchang Liao; Xiaomei Mi; Zeshui Xu
Probabilistic linguistic term set (PLTS) has been proposed to tackle qualitative information efficiently in the decision-making process to achieve computing with expressions, which can be regarded as an advanced process of computing with words. The PLTS plays an important role in decision making by providing a comprehensive way for representing complex linguistic information. Owning to its usefulness
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Parameter estimation in uncertain differential equations Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2019-09-13 Kai Yao; Baoding Liu
Parameter estimation is a critical problem in the wide applications of uncertain differential equations. The method of moments is employed for the first time as an approach for estimating the parameters in uncertain differential equations. Based on the difference form of an uncertain differential equation, a function of the parameters is proved to follow a standard normal uncertainty distribution.
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Least absolute deviations estimation for uncertain regression with imprecise observations Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2019-09-11 Zhe Liu; Ying Yang
Traditionally regression analysis answers questions about the relationships among variables based on the assumption that the observation values of variables are precise numbers. It has long been dominated by least squares, mostly due to the elegant theoretical foundation and ease of implementation. However, in many cases, we can only get imprecise observation values and the assumptions upon which the
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Using local learning with fuzzy transform: application to short term forecasting problems Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2019-09-10 Vincenzo Loia; Stefania Tomasiello; Alfredo Vaccaro; Jinwu Gao
In this paper, we formally discuss a computational scheme, which combines a local weighted regression model with fuzzy transform (or F-transform for short). The latter acts as a reduction technique on the cardinality of the learning problem, resulting in a more efficient algorithm. We tested the proposed approach first through two typical benchmark problems, that is the Hénon and the Mackey–Glass chaotic
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On product of positive L - R fuzzy numbers and its application to multi-period portfolio selection problems Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2019-09-07 Xiang Li; Hui Jiang; Sini Guo; Wai-ki Ching; Lean Yu
With the wide applications of fuzzy theory in optimization, fuzzy arithmetic attracts great attention due to its inevitability in solution process. However, the complexity of the Zadeh extension principle significantly reduces the practicability of fuzzy optimization technology. In this paper, we prove some important properties on positive L-R fuzzy numbers, and propose a new calculation method for
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Deadline-based incentive contracts in project management with cost salience Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2019-05-09 Zhihua Chen; Yanfei Lan; Ruiqing Zhao; Changjing Shang
The contractor’s procrastinating behavior owing to the psychology of cost salience exposes the project manager to the risk of time delay, which brings a significant challenge in project manager’s incentive contract design. This paper considers that a project manager pays a contractor over a menu of deadline-based incentive contracts to conduct a project which consists of two sequential tasks. The contractor
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Multiple objective optimization for systems with addition–min fuzzy relational inequalities Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2019-05-08 Sy-Ming Guu; Yan-Kuen Wu
Fuzzy relational inequalities with addition–min composition have been proposed to model the data transmission mechanism in a BitTorrent-like peer-to-peer file-sharing system. In this paper, we consider a multiple objective optimization problem which allows system manager to consider three objectives (system congestion, cost, and penalty) simultaneously. A quadratic program is then proposed for finding
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A procedure for group decision making with interval-valued intuitionistic linguistic fuzzy preference relations Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2019-05-03 Jie Tang; Fanyong Meng; Francisco Javier Cabrerizo; Enrique Herrera-Viedma
To express the uncertain preferred and non-preferred qualitative judgments of decision makers, interval-valued intuitionistic linguistic fuzzy sets (IVILFSs) are proposed in a similar way as Atanassov and Gargov’s interval-valued intuitionistic fuzzy sets. Considering the application of IVILFSs, the concept of interval-valued intuitionistic linguistic fuzzy variables (IVILFVs) is defined and a ranking
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Analysis of uncertain SIS epidemic model with nonlinear incidence and demography Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2019-05-02 Zhiming Li; Zhidong Teng
Based on uncertainty theory, this paper studies an uncertain SIS epidemic model with nonlinear incidence and demography. The solution, \(\alpha \)-paths and uncertainty distribution of uncertain model are discussed. Under threshold conditions, extinction and permanence of the disease are studied by \(\alpha \)-paths, which reveal the relationship of deterministic and uncertain models. An example is
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A single-variable method for solving min–max programming problem with addition-min fuzzy relational inequalities Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2019-04-30 Ya-Ling Chiu; Sy-Ming Guu; Jiajun Yu; Yan-Kuen Wu
In this paper, we study the min–max programming problem with n addition-min fuzzy relational inequality constraints. We prove that when the problem is feasible, an optimal solution always exists with all variables being of the same value. Based on this result, the min–max programming problem can be simplified as a single-variable optimization problem with the same optimal objective value. To solve
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Generalized extension principle for non-normal fuzzy sets Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2019-04-29 Hsien-Chung Wu
The conventional extension principle is established on the Euclidean space and defined by considering the minimum or t-norm operator in which the fuzzy sets are usually assumed to be normal. The previous work on generalized extension principle was also based on the normal fuzzy sets. Since the non-normal fuzzy sets occur frequently in practical applications, in this paper, the generalized extension
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On a class of fuzzy parametric variational inequality controlled differential equation problems in finite dimension spaces Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2018-12-03 Heng-you Lan
This work is motivated by the fact that very little is known about the fuzzy variational inequalities controlled differential equation problems in finite dimension real numeral spaces, which are studied more difficult than differential variational inequalities. It is interesting and challenging that how to solve the fuzzy variational inequalities in a fuzzy environment. The purpose of this paper is
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Applying the concept of null set to solve the fuzzy optimization problems Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2018-11-30 Hsien-Chung Wu
The concept of null set in the space of fuzzy numbers is introduced. Based on this concept, we can define two partial orderings according to the subtraction and Hukuhara difference between any two fuzzy numbers. These two partial orderings will be used to define the solution concepts of fuzzy optimization problems. On the other hand, we transform the fuzzy optimization problems into a conventional
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Group decision making based on DEA cross-efficiency with intuitionistic fuzzy preference relations Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2018-11-30 Jinpei Liu; Jingmiao Song; Qin Xu; Zhifu Tao; Huayou Chen
The aim of this paper is to investigate a novel approach to group decision making based on DEA cross-efficiency with intuitionistic fuzzy preference relations, which can avoid information distortion and obtain more credible decision making results. An interval transform function is defined, which can transform an intuitionistic fuzzy preference relation into an interval multiplicative preference relation
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A bibliometric analysis of Fuzzy Optimization and Decision Making (2002–2017) Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2018-11-29 Dejian Yu; Zeshui Xu; Wanru Wang
Fuzzy Optimization and Decision Making (FODM) is one of the influential journals in the research field of computer science and operation research, which was found in 2002. In this study, 370 publications published in FODM during 2002 and 2017 were retrieved from the Scopus database, and bibliometric methods are applied to analyze the structure of the FODM journal. First, general statistical analysis
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Numerical solution of linear inhomogeneous fuzzy delay differential equations Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2018-11-29 A. G. Fatullayev; Nizami A. Gasilov; Şahin Emrah Amrahov
We investigate inhomogeneous fuzzy delay differential equation (FDDE) in which initial function and source function are fuzzy. We assume these functions be in a special form, which we call triangular fuzzy function. We define solution as a fuzzy bunch of real functions such that each real function satisfies the equation with certain membership degree. We develop an algorithm to find the solution, and
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Uncertain time series analysis with imprecise observations Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2018-11-28 Xiangfeng Yang; Baoding Liu
Time series analysis is a method to predict future values based on previously observed values. Assuming the observed values are imprecise and described by uncertain variables, this paper proposes an approach of uncertain time series. By employing the principle of least squares, a minimization problem is derived to calculate the unknown parameters in the uncertain time series model. In addition, residual
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Portfolio selection under uncertainty by the ordered modular average operator Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2018-11-16 Hong-Quan Li; Zhi-Hong Yi; Yong Fang
In a world under uncertainty, the beliefs for the information underlie the behavioral style of portfolio decisions in portfolio management. In this work, we use the copula-based ordered modular averages (OMAs) in the calculation of the mean and variance of the assets’ returns for portfolio selection to capture the beliefs of the investors and the departure of rationality in evaluation. Specially, the
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European option pricing model based on uncertain fractional differential equation Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2018-10-22 Ziqiang Lu; Hongyan Yan; Yuanguo Zhu
In this paper, we investigate a new version of stock model under uncertain circumstances for uncertain stock markets. Firstly, solutions to some uncertain fractional differential equations are presented by employing the Mittag-Leffler function. Then, a new uncertain stock model with mean-reverting process is formulated on the basis of uncertain fractional differential equations. Finally, European option
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Fuzzy eigenvector method for deriving normalized fuzzy priorities from fuzzy multiplicative pairwise comparison matrices Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2018-09-21 Jana Siebert
The eigenvector method is one of the most used methods for deriving priorities of objects from multiplicative pairwise comparison matrices in Analytic Hierarchy Process (AHP). Fuzzy extension of AHP has been of much attention in order to capture uncertainty stemming from subjectivity of human thinking and from incompleteness of information that are integral to multi-criteria decision-making problems
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Schedule optimization under fuzzy constraints of vehicle capacity Fuzzy Optim. Decis. Making (IF 4.319) Pub Date : 2018-09-19 Yanan Zhang; Zhaopeng Meng; Yan Zheng; Anca Ralescu
The objective of designing timetables for public transportation is twofold: to ensure an efficient use of limited resources and to provide a comfortable ride for passengers. Two models for timetable optimization are investigated in this study. Model 1 uses a crisp constraint on the rate of vehicle capacity usage. Model 2 improves on model 1 by translating the crisp constraint into a fuzzy goal representing
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