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The purpose of this paper is to present how multi-criteria methods can be used in the process of National Energy Programme development and analysis of the electricity generation planning in relatively small energy systems.

Due to dependence on many input and output parameters which can be very complex and uncertain, energy systems have become extremely difficult to analyse and use of multi-criteria decision-making methods is essential. This paper presents and compares results of the analysis of electricity generation scenarios with three widely used multi-criteria methods, analytic hierarchy process (AHP), preference ranking organisation method for enrichment evaluation (PROMETHEE) and multi-attribute utility theory (MAUT).

AHP, due to its transparency and simplicity in comparison with PROMETHEE and MAUT, is the most suitable method for the analysis of the electricity generation decision alternatives in a small energy system, such as Slovenian. The case study proposed in this research confirms that transition from environment unfriendly fossil-fuelled economy to sustainable and climate friendly development requires a realistic approach, which must be based on excellent knowledge of alternative possibilities of development and especially awareness of new opportunities in exploitation of energy efficiency and renewable energy sources.

The case study presented in this research represents a repeatable and practical application of three widely used multi-criteria methods in the process of national energy policy development. It provides a methodological approach for finding realistic solutions to the problem of the future development challenges in small energy systems.

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.

The purpose of this paper is to investigate, through a comparative analysis, the applicability of lean manufacturing practices, such as value stream mapping (VSM), for productivity improvement in recycling centres (RCs) aided by multi-criteria decision analysis.

The study is carried out in five RCs that sort the municipal solid waste of Porto Alegre, one of the main cities in Brazil. Since all of the centres present their labour composed by poor communities’ members, cultural and social characteristics may represent an incremental challenge for lean implementation. Further, these centres are organised in cooperatives, in which decisions are taken through a participatory way and all their members are entitled to vote, undermining and retarding the decision-making process.

The integration of a multi-criteria decision-making tool to the lean practices enables the prioritisation of improvements, complementing the final stage of VSM. In particular, this contribution becomes especially important in cooperatives managed by community, where decisions are often complex and time-consuming. Finally, despite the increasing pressure for better performance of RCs, the existent mindset is still far from the private sector, where lean practices were conceived. Further, the findings suggest that, despite processes similarities, it is not feasible to declare the existence of a one-best practice to such scenario.

In theoretical terms, the authors demonstrate through a multi-case study the adequacy of analytic hierarchy process as a decision analysis tool complementary to the VSM, enabling a broader perspective about this subject. Concerning the practical contribution, the comprehension of the adaptation needs for lean practices implementation within the production context of solid waste RCs provides a framework with guidelines for this sector, when incorporating lean activities. Lean practitioners and eventual municipal authorities involved in improving productivity of community-managed RCs might benefit from this framework, since they will be able to emphasise the development of recommended and already tested lean practices that tend to improve their operational performance.

The aim of this paper is to introduce a newly developed multi-criteria analysis for the comparison of two grid expansion alternatives, conventional and voltage-regulated distribution transformer. The case study comprises environmental, economic, technical and social aspects.

The newly developed method decision condition Preference Ranking Organization METHod for Enrichment Evaluation (DC-PROMETHEE) combines scenario planning with the multi-attribute decision-making method PROMETHEE. DC-PROMETHEE supports the decision-maker to evaluate the total potential of an alternative considering a large number of decision conditions. The calculated performance indicator supports the decision-maker to select the best alternative.

The voltage-regulated distribution transformer shows a high overall potential in the present case study. This leads to the recommendation to the investigated distribution system operator to include the voltage-regulated distribution transformers as a grid expansion measure.

The DC-PROMETHEE can be applied to other distribution system operators by considering their individual grid topology and preferences. Other fields of application are infrastructure investments in the service area, in which expansion alternatives are evaluated in a large number of decision conditions. Examples include telecommunication, gas supply, water supply, sewage and rail networks.

This paper develops the DC-PROMETHEE approach. The DC-PROMETHEE enables the multi-criteria evaluation of a few alternatives in a large number of decision conditions.

To complete the general multi‐criteria decision‐analysis process and extend it to the process of requisitely holistic generating ideas and developing them into innovations. Also, in terms of dialectical systems thinking, to recommend the use of individual and group methods and software supporting this process.

In 1974, Mulej invented and introduced the “Dialectical System” concept (DS), and in 1998 Mulej and Kajzer fortified DS with “the Law of Requisite Holism.” The concept was well‐verified in practice, but lacked the support of quantitative versions of systems thinking. In this paper, we eliminate that deficiency: we complete and extend Belton and Stewart's general multi‐criteria decision‐analysis process to a process of generating ideas and developing them into innovations.

Methods and software supportive of creativity can help generate ideas. Multi‐criteria decision‐making (MCDM) methods can be used to complement intuition, verify ideas, and support their development into innovations. The point is in reaching the requisite holism with only a requisite effort by applied systems thinking and innovation.

Quantitative methods are considered necessary and helpful, but are not sufficient conditions for innovations or for holism.

This paper demonstrates that the modern operations research methods can help strengthen innovation and holistic thinking capacity much more than traditional ones.

The innovative aspect of this paper is that it extends a general multiple criteria decision‐analysis process to the process of generating ideas and developing them into innovations. It combines the Dialectical Systems Theory and the MCDM methods, which provides an interesting new synergy.

Pharmaceutical supply chains (PSCs) need a well-operating and faultless logistics system to successfully store and distribute their medicines. Hospitals, health institutes, and pharmacies must maintain extra stock to respond requirements of the patients. Nevertheless, there is an inverse correlation between the level of medicine stock and logistics service level. The high stock level held by health institutions indicates that we have not sufficiently excellent logistics systems presently. As such, selecting appropriate logistics service providers (drug distributors) is crucial and strategic for PSCs. However, this is difficult for decision-makers, as highly complex situations and conflicting criteria influence such evaluation processes. So, a robust, applicable, and strong methodological frame is required to solve these decision-making problems.

To achieve this challenging issue, the authors develop and apply an integrated entropy-WASPAS methodology with Fermatean fuzzy sets for the first time in the literature. The evaluation process takes place in two stages, as in traditional multi-criteria problems. In the first stage, the importance levels of the criteria are determined by the FF-entropy method. Afterwards, the FF-WASPAS approach ranks the alternatives.

The feasibility of the proposed model is also supported by a case study where six companies are evaluated comprehensively regarding ten criteria. Herewith, total warehouse capacity, number of refrigerated vehicles, and personnel are the top three criteria that significantly influence the evaluation of pharmaceutical distribution and warehousing companies. Further, a comprehensive sensitivity analysis proves the robustness and effectiveness of the proposed approach.

The proposed multi-attribute decision model quantitatively aids managers in selecting logistics service providers considering imprecisions in the multi-criteria decision-making process.

A new model has been developed to present a sound mathematical model for selecting logistics service providers consisting of Fermatean fuzzy entropy and WASPAS methods. The paper's main contribution is presenting a comprehensive and more robust model for the ex ante evaluation and ranking of providers.

Emergency situations may differ in many ways but they share some common characteristics, such as the sudden onset and the need to transparently evaluate various usually conflicting objectives. In nuclear power generation, however, emergency situations constitute a special challenge. The focus of this paper is to highlight the role of multi‐criteria decision analysis (MCDA) in nuclear emergency and recovery management on the basis of a hypothetical case study.

Multi‐attribute value theory as one field of research within MCDA is introduced. Special emphasis is placed on the modelling of the decision makers' preferences which is a crucial part in any multi‐criteria analysis. A central aim is to facilitate the preference elicitation in group decision processes.

The management of emergency situations in nuclear power generation necessitates the consideration of technical, economic, environmental, socio‐psychological and political aspects. Furthermore, various stakeholder and expert groups with diverse background knowledge and different views, responsibilities and interests are involved in such a decision‐making process. MCDA can help to take into account various incommensurable aspects and the subjective preferences of the decision makers and thus contribute to transparency and traceability of decision‐making processes. Since the preference parameters are inherently afflicted with uncertainties, thorough sensitivity analyses are important to visualise the impact of the uncertainties in an understandable way.

A new approach to sensitivity analysis is proposed, allowing one to comprehensibly visualise and communicate the impact of the uncertainties associated with the subjective preference parameters on the results of the decision analysis.

The purpose of this paper is to present a framework for evaluation and ranking of potential surrogates to select the optimum surrogates and test it for five selected social resilience indicators in a disaster context. Innovative resilience assessment approaches are required to capture key facets of resilience indicators to deepen the understanding of social resilience. Surrogates can adequately represent the target indicator that is difficult to measure, as surrogates are defined as key facets of a target indicator.

To optimize the selection of surrogates, five key evaluation criteria were used. Disaster management experts completed an online survey questionnaire and evaluated three potential surrogate options. Surrogates were then ranked using PROMETHEE, a multi-experts multi-criteria group decision analysis technique.

A framework was devised to evaluate and rank potential surrogates to assess social resilience in a disaster context. The findings revealed that the first ranked surrogate can be the most critical facet of a resilience indicator of measure. In most instances, highly experienced cohort of practitioners and policy makers have aligned their preferences of surrogates with the overall ranking of surrogates obtained in this study.

The surrogate approach can also be tested in different disaster and geographic contexts. The resilience indicators used in this study to explore surrogates are largely applicable in all contexts. However, the preference of surrogates may also vary in different contexts.

Once the surrogate is selected through an evaluation process proposed in this paper, the resilience status can be updated regularly with the help of the selected surrogate. The first ranked surrogate for each of the social resilience indicator can be applied, since the findings revealed that the first ranked surrogate can be the most critical facet in the context of the social resilience indicator being measured.

The framework and the selection of optimal surrogates will assist to overcome the conceptual and methodical challenges of social resilience assessment. The applicability of selected surrogates by practitioners and policymakers in disaster management will play a vital role in resilience investment decision-making at the community level.

The surrogate approach has been used in the fields of ecology and clinical medicine to overcome the challenges in measuring difficult to measure indicators. The use of surrogates in this study to measure social resilience indicators in a disaster context is innovative, which was not yet explored in resilience measurement in disaster management.

In this study, research problem has been designed as a fleet-based optimization problem. This paper aims to present fleet modelling with risk taxonomy. Fleet modelling has been assumed as strategic multi-criteria decision-making problem to capacity building. Capacity building risk management is an essential element within the scope of its strategy to ensure sustainable corporate performance. Optimization is a fundamental target in aviation business’ strategy and management since the manager make decisions in their multi-interrelated criteria environment. Also, aviation is a highly regulated sector, and its operational and business procedures have certain limits by both national and international authorities. For this reason, companies implement risk management for strategic optimization while performing operations in compliance with the legislation. Risk management with capacity building and resource dependency perspective applied for strategic optimization aims to capture opportunities and result in threats with minimum accidents and incidents.

The taxonomy and analytical hierarchy process (AHP) have been identified as methodologies in this research. The type of training in the high organizational performance of an approved training organization, strategy, resources and allocations with the corporate objectives, the amount and qualifications of the flight crew, their professionalism, maintenance team and licenses, hangar conditions and capacity, authority requirements and limits, region conditions, altitude and meteorology, student profile, together with a multi-criteria decision are to be considered. For each criterion, there are resources and thus resource dependence. In this study, the analytical network process method was used. In the construction of new taxonomy, specific criteria have been considered, and the analysis has been accomplished as multi-criteria decision-making problem because of the relationship and interaction between them. A number of professionals with high knowledge of the pilots and manager from Air Traffic Organization participated in the study.

The fleet modelling is both strategic and operational decision issue for training organizations. In this issue, there is a vital problem as which aircrafts should include fleet? Main criteria and sub-criteria are analyzed by AHP method and sorted according to their priorities and the fleet qualifications consisting of the most suitable aircraft/aircraft are presented. The finding and suggestions will contribute to establish sustainable organization in based on capacity building and resource dependency for managers. While analyzing main criteria, the important criteria which were found were strategic and then operational. After ordering main criteria, sub-criteria were analyzed and were multiplicated with their items. According to study findings, aircraft suitability for training model is the most important item. It follows respectively aircraft maintenance sustainability, cost of aircraft supply and faculty budget adequacy. However, operation characteristics of the square that is less important item was found. It was seen that the strategies used to manage dependencies used the bridge strategy. The results we obtained with the interviews with pilot managers are very significant in terms of resource dependence on the subject of fleet optimization. While first criterion is operational, it continues with strategic and financial criteria. After interviews with pilot managers, it was figured out that maintenance is also very important criteria. For managing this dependency, university has acquisitions, which is one of the strategy to manage dependency, rather than outsourcing. For this reason, maintenance criterion has lower importance than others. When thinking of other criteria, strategic and financial criteria have played an important role. University has tried to decrease dependency and increase sustainability.

Aircraft selection is a strategic decision of fleet modelling in both aviation business and also training organizations via influencing their corporate performance, operational performance, capacity building and their sustainability. There are some factors that limit the criteria, as research problem has been developed for approved training organizations not airlines. For this reason, our research is limited with fleet of training organizations. Our findings and suggestions may be useful for flight schools to managing their resource dependency and also to their capacity building. In this research, new taxonomy has been developed depending on training organizations’ qualifications. Airlines may improve this taxonomy to use in their decision-making process.

The fleets, which were established considering the taxonomy in this study, will be able to manage the risk of resource dependency more successfully. Pilot candidates will be able to provide a more ergonomic and higher quality education. This research and its findings will contribute to the development of organizations’ accurate and timely decision-making skills. Resource dependency may threat organizational sustainability in our research, New taxonomy and our holistic approach will support organizational efforts to achieve sustainable strategies.

New taxonomy to modelling fleet that has been developed in this research may provide contribution to approved training organizations for both managing resource dependency-based risks and to capacity building-related decision-making process. This research may serve organizations as strategic decision-making tool. And also this kind of study may contribute to improve sustainability of organizations and serve more good fleet for their pilot candidates. For these reasons, this research may create social implications, as both resource using and capacity building will make contribution for society and add value.

This research presents new risk taxonomy and criteria. Also new taxonomy and its criteria are analysed with AHP. It is thought that this research shows risk management-based approach for fleet modelling creates benefits for approved training organizations to using their limited sources effectively and efficiently. The article includes risk management and capacity building-related approach to decision-making. also, this research presents modeling which will contribute to the management field besides literature. In developing taxonomy process, the analysis has been conducted, based on expert opinions and referred to for these pairwise comparisons. Airlines managers and risk managers may examine their fleet modelling according to our taxonomy which is based on risk management.

For the purpose of decision-making in real estate portfolio management, alternatives are to be collected, assessed and prioritized. Due to the complexity of real estate markets, investment products and management processes, the respective decision situations are subject to several parameters. Multi-criteria models must be used to exactly evaluate and prioritize alternatives. Such models can be found in other economic and social areas but must be transferred or re-developed for the purposes of real estate management. The paper aims to discuss these issues.

The paper includes the transfer of the basic outranking methodology, the PROMETHEE (Preference Ranking Organization METHod für Enrichment Evaluations) method in particular, to real estate issues. Methods used outside the real estate industry are analyzed, selected and adapted by using real estate parameters (transfer approach).

Structured multi-criteria processes such as PROMETHEE are suitable for the solution of complex real estate selection decisions. The methodology with regard to the respective issues is much more consistent and efficient. PROMETHEE avoids the restriction of criteria in mathematical calculations and the restriction of quality in simple scorings.

The target system and decision criteria of investors were used exemplarily. The individual parameters and criteria can lead to new model solutions.

Multi-criteria models such as PROMETHEE stringently and transparently solve complex decision problems and alternative evaluations in real estate portfolio management. They can be developed for strategic, tactical and operative decision situations. The decision quality and verification for compliance requirements improve.

Multi-criteria models such as PROMETHEE can also be developed for social, societal and political decision situations.

First adaption of the outranking procedure PROMETHEE to a real estate decision situation in market analysis and portfolio management.