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With numerous and ambiguous sets of information and often conflicting requirements, construction management is a complex process involving much uncertainty. Decision makers may be challenged with satisfying multiple criteria using vague information. Fuzzy multi-criteria decision-making (FMCDM) provides an innovative approach for addressing complex problems featuring diverse decision makers’ interests, conflicting objectives and numerous but uncertain bits of information. FMCDM has therefore been widely applied in construction management. With the increase in information complexity, extensions of fuzzy set (FS) theory have been generated and adopted to improve its capacity to address this complexity. Examples include hesitant FSs (HFSs), intuitionistic FSs (IFSs) and type-2 FSs (T2FSs). This chapter introduces commonly used FMCDM methods, examines their applications in construction management and discusses trends in future research and application. The chapter first introduces the MCDM process as well as FS theory and its three main extensions, namely, HFSs, IFSs and T2FSs. The chapter then explores the linkage between FS theory and its extensions and MCDM approaches. In total, 17 FMCDM methods are reviewed and two FMCDM methods (i.e. T2FS-TOPSIS and T2FS-PROMETHEE) are further improved based on the literature. These 19 FMCDM methods with their corresponding applications in construction management are discussed in a systematic manner. This review and development of FS theory and its extensions should help both researchers and practitioners better understand and handle information uncertainty in complex decision problems.

The aim of this paper is to propose an optimization method for determining the emergency action, in which the compatibility between emergency alternatives and the collaborative relationship between departments are considered.

The individual emergency cost and individual emergency effect of each emergency alternative are calculated. And the collaborative emergency cost and collaborative emergency effect associated with a pair of emergency alternatives are calculated. Then, a bi-objective programming model maximizing the total emergency effect and minimizing the total emergency cost is constructed. A novel nondominated sorting genetic algorithm II (NNSGA II) is designed to solve the constructed model, subsequently. Finally, an example is given to illustrate the use of the proposed method, and the performance of NNSGA II is evaluated through a simulation experiment.

This paper proposes an effective method to manage complex emergency events that requires the coordinations of multiple departments. Also, this paper provides a new algorithm to determine an appropriate emergency action that performs well in managing both the emergency cost and emergency effect.

The findings contribute to the current methods in the field of emergency management. The method is used for dealing with the individual information of emergency alternatives and the collaborative information associated with a pair of alternatives.

This paper aims to present a simplified method to analyze the transient characteristics of a fractional-order very high frequency (VHF) resonant boost converter. The transient analytical solutions of state variables obtained by this method could be used as a guide for parameter design and circuit optimization.

The VHF converter is decoupled into a simplified equivalent circuit model and described by the differential equation. The solution of the simplified equivalent circuit model is taken as the main oscillation component of the transient state variable. And the equivalent small parameter method (ESPM) and Kalman filter technology are used to solve the differential equation of the converter to obtain the steady-state ripple component. Then, by superimposing the abovementioned two parts, the approximate transient analytical solution can be acquired. Finally, the influence of the fractional order of the energy storage elements on the transient process of the converter is discussed.

The results from the proposed method agree well with those from simulations, which indicates that the proposed method can effectively analyze the transient characteristic of the fractional-order VHF converter, and the analytical solution derived from the proposed mathematical model shows sufficient accuracy.

This paper proposes for the first time a method to analyze the transient characteristics of a fractional-order VHF resonant boost converter. By combining the main oscillated solution derived from the simplified equivalent circuit model with the steady-state solution based on ESPM, this method can greatly reduce the computation amount to estimate the transient solution. In addition, the discussion on the order of fractional calculus of energy storage components can provide an auxiliary guidance for the selection of circuit parameters and the study of stability.

It is of a great significance for the health monitoring of a liquid rocket engine to build an accurate and reliable fault prediction model. The thrust of a liquid rocket engine is an important indicator for its health monitoring. By predicting the changing value of the thrust, it can be judged whether the engine will fail at a certain time. However, the thrust is affected by various factors, and it is difficult to establish an accurate mathematical model. Thus, this study uses a mixture non-parametric regression prediction model to establish the model of the thrust for the health monitoring of a liquid rocket engine.

This study analyzes the characteristics of the least squares support vector regression (LS-SVR) machine . LS-SVR is suitable to model on the small samples and high dimensional data, but the performance of LS-SVR is greatly affected by its key parameters. Thus, this study implements the advanced intelligent algorithm, the real double-chain coding target gradient quantum genetic algorithm (DCQGA), to optimize these parameters, and the regression prediction model LSSVRDCQGA is proposed. Then the proposed model is used to model the thrust of a liquid rocket engine.

The simulation results show that: the average relative error (ARE) on the test samples is 0.37% when using LS-SVR, but it is 0.3186% when using LSSVRDCQGA on the same samples.

The proposed model of LSSVRDCQGA in this study is effective to the fault prediction on the small sample and multidimensional data, and has a certain promotion.

The original contribution of this study is to establish a mixture non-parametric regression prediction model of LSSVRDCQGA and properly resolve the problem of the health monitoring of a liquid rocket engine along with modeling the thrust of the engine by using LSSVRDCQGA.

The purpose of this paper is to analyze the influencing factors of patients’ financial burden through a case study of hospital on public‒private partnerships (PPP) model (Chaonan Minsheng Hospital of Guangdong Province) and provide some useful information to policymakers for better development of hospitals on PPP model.

There are total six indicators that are defined as patients’ financial burden, basing on the policy of “indicators of medical quality management and control on the third level large general hospital (2011 edition),” issued by Chinese Government. In total, 23 potentially influencing factors of patients’ financial burden for hospital on PPP model were chosen from the above policy. The five-year (2007‒2011) data for the above 29 indicators come from statistic department of hospital on PPP model. Grey relational analysis (GRA) was applied to analyze the influencing factors of patients’ financial burden for hospital on PPP model.

A clear rank of influencing factors of patients’ financial burden is obtained and suggestions are provided from results of GRA, which provide reference for policymakers of hospital on PPP model. The five main influencing factors of patients’ financial burden for hospital on PPP model, in sequence, are rescuing critical ill patients on emergency, rescuing critical ill inpatients, inpatient bed occupancy rate, working days per bed and medical building area.

The study on the influencing factors of patients’ financial burden for hospital on PPP model not only provides decision-making for policymaker of hospital and controlling of medical expenditure but also contributes to release patients’ financial burden for hospitals on PPP model.

The purpose of this paper is to discuss about evaluating the integrals involving B-spline wavelet on the interval (BSWI), in wavelet finite element formulations, using Gauss Quadrature.

In the proposed scheme, background cells are placed over each BSWI element and Gauss quadrature rule is defined for each of these cells. The nodal discretization used for BSWI WFEM element is independent to the selection of number of background cells used for the integration process. During the analysis, background cells of various lengths are used for evaluating the integrals for various combination of order and resolution of BSWI scaling functions. Numerical examples based on one-dimensional (1D) and two-dimensional (2D) plane elasto-statics are solved. Problems on beams based on Euler Bernoulli and Timoshenko beam theory under different boundary conditions are also examined. The condition number and sparseness of the formulated stiffness matrices are analyzed.

It is found that to form a well-conditioned stiffness matrix, the support domain of every wavelet scaling function should possess sufficient number of integration points. The results are analyzed and validated against the existing analytical solutions. Numerical examples demonstrate that the accuracy of displacements and stresses is dependent on the size of the background cell and number of Gauss points considered per background cell during the analysis.

The current paper gives the details on implementation of Gauss Quadrature scheme, using a background cell-based approach, for evaluating the integrals involved in BSWI-based wavelet finite element method, which is missing in the existing literature.

The purpose of this paper is to explore the dynamic interdependence structure and risk spillover effect between the Chinese stock market and the US stock market.

This paper mainly uses the multivariate R-vine copula-complex network analysis and the multivariate R-vine copula-CoVaR model and selects stock price indices and their subsector indices as samples.

The empirical results indicate that the Energy, Materials and Financials sectors have leading roles in the interdependent structure of the Chinese and US stock markets, while the Utilities and Real Estate sectors have the least important positions. The comprehensive influence of the Chinese stock market is similar to that of the US stock market but with smaller differences in the influence of different sectors of the US stock market on the overall interdependent structure system. Over time, the interdependent structure of both stock markets changed; the sector status gradually equalized; the contribution of the same sector in different countries to the interdependent structure converged; and the degree of interaction between the two stock markets was positively correlated with the degree of market volatility.

This paper employs the methods of nonlinear cointegration and the R-vine copula function to explore the interactive relationship and risk spillover effect between the Chinese stock market and the US stock market. This paper proposes the R-vine copula-complex network analysis method to creatively construct the interdependent network structure of the two stock markets. This paper combines the generalized CoVaR method with the R-vine copula function, introduces the stock market decline and rise risk and further discusses the risk spillover effect between the two stock markets.

The newsvendor problem is fundamental to many operations management models. The problem focuses on the trade-off between the gains from satisfying demand and losses from unsold products. The newsvendor model and its extensions have been applied to various areas, such as production plan and supply chain management. This chapter examines the study about newsvendor problem. In this research, there is a review of the contributions for the multiproduct newsvendor problem. It focuses on the current literature concerning the mathematical models and the solution methods for the multiitem newsvendor problems with single or multiple constraints, as well as with the risks. The objective of this research is to go over the newsvendor problem and bring into comparison different newsvendor models applied to the flower industry. A few case studies are described addressing topics related to the newsvendor problem such as discounting and replenishment policies, inventory inaccuracies, or demand estimation. Three newsvendor models are put into practice in the field of flower selling. A full database of the flowers sold by an anonymous retailer is available for the study. Computational experiments for practical example have been conducted with use of the CPLEX solver with AMPL programming language. Models are solved, and an analysis of different circumstances and cases is accomplished.

The purpose of this paper is to identify the risk factors that affect aquatic product quality in the “farming-supermarket docking” condition. This paper investigates how the investment scale can affect earnings and aquatic product quality assurance level. Also, it aims to determine an effective method for increasing aquatic product assurance level, coordinate the supply chain and improve management of the entire supply chain.

The authors construct a coordination model for quality risk control of the aquatic supply chain by simulating the model in a tilapia supply chain using the case study method. They applied Karush–Kuhn–Tucker conditions to analyze upstream enterprises (breeding base) and downstream enterprises (corresponding supermarket) under the conditions of sufficient or insufficient funds, Further, they consider the relationships among revenue, optimum quality assurance and investment scale at different capital positions; discuss the best cooperation conditions in four cases; and draw conclusions on ways to control quality risk.

The proposed coordination model is found to be effective in controlling aquatic product quality risk. The simulation results show that when the enterprise funds are sufficient, the sales prices, product freshness, quality assurance ability, collaboration and quality test ability have a positive influence on quality assurance level, whereas coefficient and price sensitivity have a negative influence on it. Additionally, it can obtain high-quality assurance levels and earnings in both breeding bases and supermarkets under the condition of adequate investment.

The study built a coordination model combined with the characteristics of the aquatic supply chain by adding the quality penalty mechanism, product freshness parameters and cost function in the “farming-supermarket docking” mode into the traditional principal–agent model. Research results are beneficial to enhancing the quality assurance level of the aquatic supply chain and improving the coordination level of the supply chain.