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The multiple objective decision making problem arises when two or more non‐comparable objective functions are to be simultaneously optimised. There is a definite trend towards utilising interactive techniques for solving the multiple objective decision making problem. Interactive techniques allow the involvement of the DM throughout the decision process. In this paper we first provide a brief overview of multiple objective decision making, and then give a survey of literature dealing with interactive multiple objective decision making from 1965 to 1988.

Most decision-making problems in construction are complex and difficult to solve, as they involve multiple criteria and multiple decision makers in addition to subjective uncertainties, imprecisions and vagueness surrounding the decision-making process. In many instances, the decision-making process is based on linguistic terms rather than numerical values. Hence, structured fuzzy consensus-reaching processes and fuzzy aggregation methods are instrumental in multi-criteria group decision-making (MCGDM) problems for capturing the point of view of a group of experts. This chapter outlines different fuzzy consensus-reaching processes and fuzzy aggregation methods. It presents the background of the basic theory and formulation of these processes and methods, as well as numerical examples that illustrate their theory and formulation. Application areas of fuzzy consensus reaching and fuzzy aggregation in the construction domain are identified, and an overview of previously developed frameworks for fuzzy consensus reaching and fuzzy aggregation is provided. Finally, areas for future work are presented that highlight emerging trends and the imminent needs of fuzzy consensus reaching and fuzzy aggregation in the construction domain.

Environmental decision making involving multiple stakeholders can benefit from the use of a formal process to structure stakeholder interactions, leading to more successful outcomes than traditional discursive decision processes. There are many tools available to handle complex decision making. Here we illustrate the use of a multicriteria decision analysis (MCDA) outranking tool (PROMETHEE) to facilitate decision making at the watershed scale, involving multiple stakeholders, multiple criteria, and multiple objectives. We compare various MCDA methods and their theoretical underpinnings, examining methods that most realistically model complex decision problems in ways that are understandable and transparent to stakeholders.

Travel interests of tourists during pandemics and outbreaks are reduced due to the prevalence of fear. It induces lifestyle changes, which may hinder efforts to recover the tourism value chain during post-COVID-19 lockdowns. Subscribing to domestic travel and domestic tourism is deemed to mitigate fear and gradually reopen the tourism industry. Although a crucial initiative, evaluating the perceived degree of exposure of tourists to COVID-19 in tourist sites operating under domestic tourism has not been fully explored in the emerging literature, which forms the main departure of this work.

The problem domain is addressed by adopting multiple criteria sorting method – the VIKORSORT. To demonstrate such application, with 221 survey participants, 35 tourist sites in a province in the central Philippines struggling to revive the tourism industry are evaluated under six attributes that characterize tourists' exposure to COVID-19. To assess its efficacy, the performance of the VIKORSORT is compared to other distance-based multiple criteria sorting methods (i.e. TOPSIS-Sort and CODAS-SORT).

Results show that proximity and volume of tourist arrivals are considered on top of the priority list of attributes. The use of VIKORSORT yields the assignment of 27 sites to the “moderate exposure” class, and eight under the “high exposure” class, with no tourist site assigned to the “low exposure” class. Sorting the tourist sites reveals some observations that tourists prefer sites (1) with open spaces, (2) with activities having limited group dynamics, (3) that are nature-based, and (4) with tourist arrivals that are not relatively high, with enough land area to practice social distancing. In addition, the assignments of the VIKORSORT with TOPSIS-Sort and CODAS-SORT are consistent at least 90% of the time, demonstrating its efficacy in addressing multiple criteria sorting problems.

This work provides an integrative approach in evaluating tourist sites in view of tourism recovery during pandemics. The findings offer crucial insights for the primary stakeholders (i.e. government, tourist operators, and tourists) in planning, resource allocation decisions, and policy formulation. Policy insights are offered, as well as avenues for future works.

Corporate social responsibility has gradually become an essential enterprise responsibility under stakeholders’ expectations. Employee care strategies involve both qualitative and quantitative factors and are receiving special attention with the advent of the information age. In previous studies, a company’s policy of employee care may not fit with the needs of the employees. Consequently, the purpose of this paper is to investigate enterprises’ employee care from the employee’s perspective by adopting a hybrid multiple attribute decision making (MADM) model.

This study is based on 159 interviews with senior employees and/or department managers using a survey questionnaire. This study uses the MADM model to conduct the analysis. First, this research study used Decision-Making Trial and Evaluation Laboratory (DEMATEL) to construct an influential network relations map of the 4 dimensions and 13 criteria of employee care. Second, this study uses DEMATEL-based Analytic Network Process to conduct a weight analysis for each dimension and criterion. Third, this study uses VIKOR to calculate employees’ level of satisfaction as well as the gap from the “aspired level.”

The results of the study revealed the critical factors influencing employee care and proposed a systematic plan to be used as a reference for improvement. The improvement sequence revealed the following order: Equal employment opportunities→Good industrial relations and benefits→Responsibility to train and educate employees→Occupational health and safety. The empirical results showed there was still 35 percent room for improvement in the enterprises’ implementation policy of employee care.

The implementation of employee care has become an important issue for corporations since it helps to sustain and to increase an enterprise’s competitiveness in the business environment. However, the extant literature on employee care comes from enterprises’ perspectives instead of from employees’ perspectives. This research investigates the key factors of employee care and successfully shows MADM to be an effective model for the planning and implementation of corporate social responsibilities’ employee care from the perspective of employees.

Decision makers in the service industry must effectively cope with queuing problems, service capacity optimization, service efficiency and service quality problems. This study proposes a computer simulation‐enabled MCDM framework that integrates computer simulation analysis, Taguchi method, expert opinion and multiple criteria decision making (MCDM) to assist decision makers in coping with decision problems. In this framework, Taguchi method is adopted to reduce the time required for the simulation experiment. Computer simulation analysis is adopted to obtain useful information for rapid decision‐making without interrupting actual production. MCDM is used to select the optimal alternative. The illustrative result is extremely promising.

This paper shows how the evolutionary structural optimization (ESO) algorithm can be used to achieve a multiple criterion design for a structure in a thermal environment. The proposed thermal ESO procedure couples an evolutionary iterative process of a finite element heat conduction solution and a finite element thermoelastic solution. The overall efficiency of material usage is measured in terms of the combination of thermal stress levels and heat flux densities by using a combination strategy with weighting factors. The ESO method then works by eliminating from the structural domain under‐utilized material. In this paper, a practical design example of a printed circuit board substrate is presented to illustrate the capabilities of the ESO algorithm for thermal design optimization in multiple load environments.

The purpose of this paper is to review the literature which focuses on four major higher education decision problems. These are: resource allocation; performance measurement; budgeting; and scheduling.

Related articles appearing in the international journals from 1996 to 2005 are gathered and analyzed so that the following three questions can be answered: “What kind of decision problems were paid most attention to?”; “Were the multiple criteria decision‐making techniques prevalently adopted?”; and “What are the inadequacies of these approaches?”

Based on the inadequacies, some improvements and possible future work are recommended, and a comprehensive resource allocation model is developed taking account of these factors. Finally, a new knowledge‐based goal programming technique which integrates some operations of analytic hierarchy process is proposed to tackle the model intelligently.

Higher education has faced the problem of budget cuts or constrained budgets for the past 30 years. Managing the process of the higher education system is, therefore, a crucial and urgent task for the decision makers of universities in order to improve their performance or competitiveness.

There are many investigations in design methodologies, but there are also divergences and convergences as there are so many points of view. This study aims to evaluate to corroborate and deepen other researchers’ findings, dissipate divergences and provide directing to future work on the subject from a methodological and convergent perspective.

This study analyzes the previous reviews (about 15 reviews) and based on the consensus and the classifications provided by these authors, a significant sample of research is analyzed in the design for additive manufacturing (DFAM) theme (approximately 80 articles until June of 2017 and approximately 280–300 articles until February of 2019) through descriptive statistics, to corroborate and deepen the findings of other researchers.

Throughout this work, this paper found statistics indicating that the main areas studied are: multiple objective optimizations, execution of the design, general DFAM and DFAM for functional performance. Among the main conclusions: there is a lack of innovation in the products developed with the methodologies, there is a lack of exhaustivity in the methodologies, there are few efforts to include environmental aspects in the methodologies, many of the methods include economic and cost evaluation, but are not very explicit and broad (sustainability evaluation), it is necessary to consider a greater variety of functions, among other conclusions

The novelty in this study is the methodology. It is very objective, comprehensive and quantitative. The starting point is not the case studies nor the qualitative criteria, but the figures and quantities of methodologies. The main contribution of this review article is to guide future work on the subject from a methodological and convergent perspective and this article provides a broad database with articles containing information on many issues to make decisions: design methodology; optimization; processes, selection of parts and materials; cost and product management; mechanical, electrical and thermal properties; health and environmental impact, etc.

Multi‐criteria decision making exists in the daily lives with broad application backgrounds. Sometimes because of incomplete information, the weights can only be estimated subjectively, which leads to an unsatisfactory result. The purpose of this paper is to describe an interactive technique to decide multi‐criteria weights by multiple decision makers in the condition of incomplete information by means of virtual environment.

The procedure assumed a problem with n criteria and r decision makers. The algorithms employed are presented.

It was found that the proposed framework is an effective weight‐deciding tool; the procedure quickly locates excellent compromise weights in a series of test problems.

The methodology helps decision makers determine a most preferred final solution by the virtual environment especially when there is incomplete information. The procedures provide a mechanism to guide the decision makers towards an acceptable compromise solution, without requiring excessive decision maker input. Studies show that the procedure performs well in terms of solution quality, simplicity, computational requirements, convergence and flexibility.