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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.

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.

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.

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 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.

The purpose of this paper is to perform a systematic review on the application of different multi-criteria decision-making (MCDM) methods in solving the site selection problem across multiple problem domains. The domains are energy generation, logistics, public services and retail facilities. This study aims to answer the following research questions: Which evaluating criteria were used for each site selection problem domain? Which MCDM methods were frequently applied in a particular site selection problem domain?

The goals of the systematic review were to identify the evaluating criteria as well as the MCDM method used for each problem domain. A total of 81 recent papers (2014–2018) including 32 papers published in conference proceedings and 49 journal articles from various databases including IEEE Xplore, PubMed, Springer, Taylor and Francis as well as ScienceDirect were evaluated.

This study has shown that site selection for energy generation facilities is the most active site selection problem domain, and that the analytic hierarchy process (AHP) method is the most commonly used MCDM method for site selection. For energy generation, the criteria which were most used were geographical elements, land use, cost and environmental impact. For logistics, frequently used criteria were geographical elements and distance, while for public services population density, supply and demand, geographical layout and cost were the criteria most used. Criteria useful for retail facilities were the size (space) of the store, demographics of the site, the site characteristics and rental of the site (cost).

This study is limited to reviewing papers which were published in the years 2014–2018 only, and only covers the domains of energy generation, logistics, public services and retail facilities.

MCDM is a viable tool to be used for solving the site selection problem across the domains of energy generation, logistics, public services and retail facilities. The usage of MCDM continues to be relevant as a complement to machine learning, even as data originating from embedded IoT devices in built environments becomes increasingly Big Data like.

Previous systematic review studies for MDCM and built environments have either focused on studying the MCDM techniques itself, or have focused on the application of MCDM for site selection in a single problem domain. In this study, a critical review of MCDM techniques used for site selection as well as the critical criteria used during the MCDM process of site selection was performed on four different built environment domains.

Multi-criteria decision-making (MCDM) techniques are decision support systems that provide systematic approaches to solve hospitality and tourism (H&T) problems while minimizing the risk of failure. However, less is known about the application of MCDM techniques in H&T research. This study aims to systematically assess the use of MCDM techniques in H&T research to classify its current application and determine its application potential for H&T research.

This study used bibliometric analysis to examine all published MCDM studies focused on H&T industries, since 1997. In addition, topic modelling was used to discover key concepts. Finally, top cited studies in terms of total citations per year and total citations were qualitatively reviewed for more insights.

The findings revealed an ongoing interest in applying MCDM techniques in H&T research. Specifically, the extension of fuzzy theory in MCDM techniques is burgeoning among H&T researchers. However, a certain number of MCDM techniques seem to be ignored in this field with a repetitive application of MCDM techniques in particular areas.

The data for the current research was solely retrieved from Scopus and other databases were not included. Therefore, future research is called for to re-examine the study by considering data from various databases.

This study contributes to extant H&T literature by identifying the most prolific and influential countries, journals, publications and trends by applying MCDM techniques in H&T research, and elucidating the implications and characteristics of MCDM techniques in H&T research.

The purpose of this paper is (1) to review, analyze and assess the existing literature on lean tools selection studies published from 2005 to 2021; (2) to identify the limitations faced by previous studies; and (3) to suggest future works that are necessary to facilitate the selection of lean tools.

A systematic approach was used in order to identify, collect and select the articles. Several keywords related to the selection of lean tools were used to collect articles from different Scopus indexed journals. Next, the study systematically reviewed and analyzed the selected papers to identify the lean tools' selection method and discussed its features and limitations.

An analysis of the results showed that previous studies have adopted two types of methods for selecting lean tools. First, there are various traditional methods being used. Second, multi-criteria decision-making (MCDM) methods were commonly used in previous studies, such as the multi-objective decision-making method (MODM), single multi-attribute decision-making (MADM) methods and hybrid (MCDM). Moreover, the study revealed that the lean tools' selection methods in previous studies were based on evaluating the relationship between either lean tools and performance metrics or lean tools and waste, or both.

In terms of its theoretical value, the study is considered as an extension of the previous researches performed on this topic by determining and analyzing the features of the most selection methods of lean tools. Unlike previous review papers, this review had considered discussing and analyzing the characteristics and limitations of these methods. Section 2.2 of this paper reviewed some of the categories of MCDM methods as well as some of the traditional methods used in the selected previous studies. Section 2.1 of this paper explained the concept of lean management and its application benefits. Further, only three sectors were covered by the previous studies in this review paper. This study also provided recommendations for future research. Therefore, it provided researchers with a good conception of how to conduct the studies on lean tools selection. Besides, knowing the methods used in previous studies can help researchers develop new methods to select the best set of lean tools. That is, this study provided and advanced the existing knowledge base for researchers concerning lean tools selection, especially there is limited availability of review papers on this topic. Moreover, the study showed researchers the importance of the relationship between lean tools and indicators or/and performance indicators to determine the appropriate set of lean tools so that the results of future studies will be more realistic and acceptable.

Practically, manufacturers face a significant challenge when selecting proper lean tools. This study may enhance managers, manufacturers and company's knowledge to identify most of the methods used to choose the best set of lean tools and what are the advantages, disadvantages and limitations of these methods as well as the latest studies that have been adopted in this topic. That means this study can direct companies to prioritize the application of lean tools depending on either the manufacturing performance metrics or/and manufacturing wastes so that they avoid incorrect application of lean tools, which will add more non-value added activities to operations. Therefore companies can decrease the time and cost losses and enhancing the quality and efficiency of the performance. Correctly implementing the best set of lean tools in companies will lead in general to correctly applying lean management in corporations. Therefore, these lean tools can boost the economic aspect of companies and society through reducing waste, improving performance indicators, preserving time and cost, achieving quality, efficiency, competitiveness, boosting employee income and improving the gross domestic product. The correct lean tool selection reduces customer complaints and employee stress and improves work conditions, health, safety and labor wellbeing. Besides, the correct lean tools selection improves materials usage, energy usage, water usage and decreases liquid wastes, solid wastes and air emissions. As a result, the right selection of lean tools will have positive effects on both the environment and society. The study may also encourage manufacturers and researchers to adopt studies on lean tools selection in small- and medium-sized companies because the study referred to the importance and participation of these kinds of companies in a large proportion of the economy of developing countries. Further, the study may encourage some countries that have not previously adopted this type of study, academically and industrially to conduct lean tools selection studies.

As mentioned previously, the correct lean tool selection reduces customer complaints and employee stress and improves work conditions, health, safety and labor wellbeing. The proper lean tools selection improves materials usage, energy usage, water usage and decreases liquid wastes, solid wastes and air emissions. As a result, the right choice of lean tools will positively affect both the environment and society.

The study expanded the efforts of previous studies concerning lean management features. It provided an accurate review of most lean tools selection studies published from 2005 to 2021 and was not limited to the manufacturing sector. It further identified and briefly described the selection methods concerning lean tools adopted in each paper.

The purpose of this paper is to propose a new MCDM method called ranking based on optimal points (RBOP).

By employing two abstract groups of alternatives as the optimum alternatives and an optimal alternative, in order to offer the most desirable alternative, RBOP imitates human behavior in the decision-making process. RBOP policy is to find the best alternative through measuring alternatives distances from optimum alternatives and optimal alternative, thus, the best alternative must be sitting on the closest distance to its optimum points and the closest distance to the optimal points simultaneously.

In this paper, the author introduced a ten-step gray form of RBOP which is applied in a case of buying running shoes and results compared to the existing MCDM methods. Results showed the considerable differences.

Generally, in order to select the best alternative(s), and to aid decision makers (DMs) to make better decisions for the real-world problems, MCDM methods evaluate a number of alternatives via a number of criteria through the proposed mathematical algorithms. Frequently, for the direct impact of the DMs on the decision-making process, MCDM methods have inflexible algorithms. They only allow DMs to make an impact on the criteria analysis. The inflexibility emerges as a problem when perfect information is available for DMs and MCDM final results are not desirable. The process of the new method completely depends on DMs’ decisions, their interpretation of the periphery and their personal impressions. Hence, the output of RBOP is not necessarily the best alternative, but it offers the most desirable alternative to DM.