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Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

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.

This paper aims to classify journal papers in the context of hybrid quality function deployment QFD and multi-criteria decision-making (MCDM) methods published during 2004–2021.

A conceptual classification scheme is presented to analyze the hybrid QFD-MCDM methods. Then some recommendations are given to introduce directions for future research.

The results show that among all related areas, the manufacturing application has the most frequency of published papers regarding hybrid QFD-MCDM methods. Moreover, using uncertainty to establish a hybrid QFD-MCDM the relevant papers have been considered during the time interval 2004–2021.

There are various shortcomings in conventional QFD which limit its efficiency and potential applications. Since 2004, when MCDM methods were frequently adopted in the quality management context, increasing attention has been drawn from both practical and academic perspectives. Recently, the integration of MCDM techniques into the QFD model has played an important role in designing new products and services, supplier selection, green manufacturing systems and sustainability topics. Hence, this survey reviewed hybrid QFD-MCDM methods during 2004–2021.

For some specific multi-criteria decision-making (MCDM) problems, especially in emergency situations, because of the feature of criteria and other fuzzy factors, it is more appropriate that values of different criteria are expressed in their correspondingly appropriate value types. The purpose of this paper is to build a multi-criteria group decision-making (MCGDM) model dealing with heterogeneous information based on distance-based VIKOR to solve emergency supplier selection in practice appropriately and flexibly, where a compromise solution is more acceptable and suitable.

This paper extends the classical VIKOR to a generalized distance-based VIKOR to handle heterogeneous information containing crisp number, interval number, intuitionistic fuzzy number and hesitant fuzzy linguistic value, and develops an MCGDM model based on the distance-based VIKOR to handle the multi-criteria heterogeneous information in practice. This paper also introduces a parameter called non-fuzzy degree for each type of heterogeneous value to moderate the computation on aggregating heterogeneous hybrid distances.

The proposed distance-based model can handle the heterogeneous information appropriately and flexibly because the computational process is directly operated on the heterogeneous information based on generalized distance without a transformation process, which can improve the decision-making efficiency and reduce information loss. An example of emergency supplier selection is given to illustrate the proposed method.

This paper develops an MCGDM model based on the distance-based VIKOR to handle heterogeneous information appropriately and flexibly. In emergency supplier selection situations, the proposed decision-making model allows the decision-makers to express their judgments on criteria in their appropriate value types.

The purpose of this paper is to develop some weight determining methods for hesitant fuzzy multi-criterion decision making (MCDM) in which the preference information on attributes is collected over different periods.

Based on the proposed weight determining methods and dynamic hesitant fuzzy aggregation operators, an approach is developed to solve the hesitant fuzzy multi-stage multi-attribute decision-making problem where all the preference information of attributes over different periods is represented in hesitant fuzzy values.

In order to determine the weights associated with dynamic hesitant fuzzy operators, the authors propose the improved maximum entropy method and the minimum average deviation method.

This paper does not consider the multi-stage multi-criteria group decision-making problem.

An example concerning the evaluation of rangelands is given to illustrate the validation and efficiency of the proposed approach. It should be stated that the proposed approach can also be implemented into other multi-stage MCDM problems.

The concept of hesitant fuzzy variable (HFV) is defined. Some operational laws and properties of the HFVs are given. Moreover, to fuse the multi-stage hesitant fuzzy information, the aggregation operators of hesitant fuzzy sets are extended to that of the HFVs.

System dynamics has several applications in the built environment, and few studies indicate that it has potential in evaluating sustainability. Sustainability in the built environment involves numerous entities and multiple trade-offs. Hence, a Multi-Criteria Decision-Making (MCDM) method is ideal for promoting sustainability-based decision-making in the built environment. Therefore, this study integrates system dynamics with an MCDM method to enable the sustainability assessment by capturing the time-induced dynamic changes affecting long time sustainability performance of buildings.

Conventional sustainability assessment tools in the built environment lack a comprehensive evaluation that balances the needs of the society, economy and environment. This study develops a system dynamics-based framework to enable sustainability-conscious decision-making and policy analysis in the built environment.

Various material, technology and water-related policies specific to the buildings are investigated for a case study building. It is found that the effect of penetration of renewable energy technology to the tune of 80% and above in the energy mix is a much superior policy in sustainability improvement in comparison to material and water-related policies. The study also demonstrates the effect of weights assigned for the different indicators on sustainability-based decisions.

The study provides a methodological framework for a sustainability-based decision support system for the built environment that enables dynamic performance evaluation by coupling system dynamics with the MCDM. This coupling further strengthens system dynamics as a decision-making and policy analysis for sustainability evaluation in the built environment.

Driven by motivation of quality enhancement and brand reputation promotion, automotive industries try to improve product quality and customer satisfaction by performing quality pilot programs continuously. The purpose of this paper is to develop a dynamic model to select the improvement quality pilot program from competitive candidates based on dynamic customers’ feedback.

An extended dynamic multi-criteria decision-making method is developed by embedding dynamic triangular fuzzy weighting average operators into fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, and the novel evaluation indicator “ζ” is introduced to reflect prioritization performance.

The two evaluation indicators (Q and “ζ” ) assist quality managers to identify the best program with respect to multiple conflicting criteria and the best choice based on these two indexes shows high conformity. Besides, ranking sequences obtained by “ζ” can avoid the dilemma that there are several candidates with top priority calculated by comprehensive group utility value Q.

The dynamic MCDM method has been applied into the quality improvement procedure in Chinese domestic auto factories and contributes to highly efficient promotion.

Few dynamic models on pilot program selection for quality improvement based on dynamic customers’ feedback, this study deals with the dynamic promotion by an extended fuzzy VIKOR method and presents a case application.

Nowadays, cloud platforms are used in many fields, including e-commerce, web applications, data storage, healthcare, gaming, mobile social networks, etc. However, security and privacy are still two significant concerns in this area. The target of this paper is to present a system for trust management in industrial cloud computing using the multi-criteria decision making (MCDM) approach. MCDM techniques have been developed to accommodate a wide range of applications. As a result, hundreds of approaches have been generated with even minor variations on current approaches spawning new study fields.

Cloud computing provides a fully scalable, accessible and flexible computing platform for various applications. Due to the multiple applications that cloud computing has found in numerous life features, users and providers have considered providing security in cloud communications. Due to its distributive nature, dynamic space and lack of transparency in performing cloud computing, it faces many challenges in providing security. For security improvement, trust management can play a very influential role. This paper proposes a generic analytical methodology that uses a series of assessment criteria to evaluate current trust management testing prototypes in industrial cloud computing and related fields. The authors utilize a MCDM approach in the present article. Due to the multi-dimensionality of the sustainability objective and the complexities of socio-economic and biophysical processes, MCDM approaches have become progressively common in decision-making for sustainable energy.

The results of comparing and evaluating the performance of this model show its ability to manage trust and the ability to adapt to changes in the behavior of service providers quickly. Using a simulation, all results are confirmed. The results of simulations and evaluation of the present paper indicate that the proposed model provides a more accurate evaluation of the credibility of cloud service providers than other models.

The number of cloud services and customers is vast and extremely competitive in cloud environments, where novel cloud services and customers can join at any time, while others can withdraw whenever they want. Because of cloud services' highly dynamic and dispersed design, trust management mechanisms must be highly flexible to obtain feedback and update trust outcomes as quickly as possible. The model presented in this article tries to improve users' trust in the cloud industry.

Using a method (MCDM) to find the best trust management solution based on user experience in industrial cloud computing is the novelty of this paper.

The purpose of this paper is to discuss the advantage of a combinatory methodology presented in this study. The paper suggests that the comparison with results of previously developed methods is in high agreement.

This paper introduces a combined compromise decision-making algorithm with the aid of some aggregation strategies. The authors have considered a distance measure, which originates from grey relational coefficient and targets to enhance the flexibility of the results. Hence, the weight of the alternatives is placed in the decision-making process with three equations. In the final stage, an aggregated multiplication rule is employed to release the ranking of the alternatives and end the decision process.

The authors described a real case of choosing logistics and transportation companies in France from a supply chain project. Some comparisons such as sensitivity analysis approach and comparing to other studies and methods provided to validate the performance of the proposed algorithm.

The algorithm has a unique structure among MCDM methods which is presented for the first time in this paper.