Describing acceptable objects by means of Sugeno integrals

The cube of opposition is a logical structure that underlies many information representation settings. When applied to multiple criteria decision, it displays various possible aggregation attitudes. Situations are usually assessed by combinations of properties they satisfy, but also by combinations of properties they do not satisfy. The cube of opposition applies to qualitative evaluation when criteria are weighted as well as in the general case where any subset of criteria may be weighted for expressing synergies between them, as for Sugeno integrals. Sugeno integrals are well-known as a powerful qualitative aggregation tool which takes into account positive synergies between properties. When there are negative synergies between properties we can use the so-called desintegral associated to the Sugeno integral. The paper investigates the use of the cube of opposition and of the if-then rules extracted from these integrals and desintegrals in order to better describe acceptable situations.

Sugeno integrals are well-known qualitative aggregation functions in multiple criteria decision making. They return a global evaluation between the minimum and the maximum of the input criteria values. They can model sophisticated aggregation schemes through a system of priorities that applies to any subset of criteria and can take into account some kind of synergy inside subsets of criteria. Although a given Sugeno integral specifies a particular way of implicitly describing a set of entities reaching some global satisfaction level, it is hard to figure out what is the underlying explicit meaning of such an integral in practice (even if the priority level associated to each subset of criteria has a precise meaning). The paper proposes an answer to this problem. Any capacity on a finite set can be represented by a special possibilistic logic base containing positive prioritised clauses, and conversely any possibilistic logic base can represent a set-function. Moreover, Sugeno integral can be represented by a possibilistic logic base expressing how it behaves (thanks to a mapping between the scale and a set of logical atoms reflecting the different values for each criterion). Viewing a Sugeno integral as a set of prioritized logically expressed goals has not only the advantage to make the contents of a Sugeno integral more readable, but it also prompts Sugeno integrals into the realm of logic, and makes it possible to define entailment between them.

Background: Multi-criteria decision analysis (MCDA) is a decision-making tool that can take into account multidimensional factors and enables comparison of (medical) technologies by combining individual criteria into one overall appraisal. The MCDA approach has slowly gained traction within Health Technology Assessment (HTA) and its elements are gradually being incorporated into HTA across Europe. Several groups of scientists have proposed MCDA approaches targeted toward orphan drugs and rare diseases by including criteria specific to rare diseases. The goal of this article is to provide an overview of the current state of knowledge and latest developments in the field of MCDA in HTA for orphan drugs, to review existing models, their design characteristics, as well as to identify opportunities for further model improvement.Methods: A systematic literature search was conducted in January 2018 using four databases: MEDLINE (Pubmed), EBSCO HOST, EMBASE, and Web of science to find publications related to use of MCDA in the rare disease field (keywords: MCDA/orphan drug/rare disease and synonyms). Identified MCDA models were analyzed, e.g., structure, criteria, scoring, and weighting methodology.Results: Two hundred and eleven publications were identified, of which 29 were included after removal of duplicates. 9 authors developed own MCDA models, 7 of which based on literature reviews intended to identify the most important and relevant decision criteria in the model. In 13 publications (8 models) weights were assigned to criteria based on stakeholder input. The most commonly chosen criteria for creation of the MCDA models were: comparative effectiveness/efficacy, the need for intervention, and disease severity. Some models have overlapping criteria, especially in the treatment cost and effectiveness areas.Conclusions: A range of MCDA models for HTA have been developed, each with a slightly different approach, focus, and complexity, including several that specifically target rare diseases and orphan drug appraisal. Models have slowly progressed over the years based on pilots, stakeholder input, sharing experiences and scientific publications. However, full consensus on model structure, criteria selection and weighting is still lacking. A simplification of the MCDA model approach may increase its acceptance. A multi-stakeholder discussion on fundamental design and implementation strategies for MCDA models would be beneficial to this end.

Decision-making tools have become a prominent methodology in watershed management for many years due to the complexity of environmental systems and requirement for multi-disciplinary expertise. Multi-Criteria Decision Analysis (MCDA) is a systematic methodology, which combines hierarchical structures of a problem and priorities for the alternatives in many fields. This study reviews MCDA applications in pollution risk assessment in the abiotic environments of watersheds for multi-pollutants. Over 80 papers published between 2000 and 2021 are identified in three categories of the Web of Science Core Collection database: “Environmental Sciences”, “Environmental Studies”, and “Water Resources”. The publications are further classified according to different environmental compartments: surface water, groundwater, and soil to investigate MCDA applications in these matrices. Finally, the distribution of the publications according to contaminants and MCDA methods used are also examined. The results reveal that the number of the studies focusing on pollution risk assessment within watersheds has been significantly increasing, especially over the last decade. However, there are still limited MCDA applications linking environmental compartments. Despite several MCDA studies focusing on the vulnerability of watersheds to multiple pollutants, studies related with emerging pollutants are scarce. Moreover, compared to non-point source pollution, studies adopting MCDA to investigate pollutant concentrations coming from point sources are relatively few. According to the overall distributions of MCDA methods, Analytic Hierarchy Process, a commonly found method in the literature that adopts a technique of pairwise comparison to prioritize criteria of prominence, dominates 34% of the publications.

Multi-criteria Decision Making (MCDM) involves evaluating alternatives based on a comprehensive set of conflicting criteria, often requiring the involvement of varied decision makers. This has led to the emergence of stakeholder-based multi-criteria group decision-making (MCGDM) frameworks. However, traditional MCGDM frequently overlooks the interactions and trade-offs among different actors and criteria. The Multi-actor Multi-criteria Analysis (MAMCA), developed in 2000, provides a transparent decision-making process explicitly considering these interrelationships. It allows diverse stakeholder groups to represent their priorities, thereby enhancing their understanding of their own and others’ positions. Over the past two decades, MAMCA has seen a significant rise in popularity and has been widely applied in diverse contexts, proving valuable as both a decision-making and stakeholder engagement tool. However, our analysis of publications on cases in which MAMCA was applied over the years shows that considerable variation exists in the overall process approach, contingent upon the specific goals and context. To address these variations, this paper proposes a modularized MAMCA structure, complemented by systematic application guidelines, to aid future users in navigating the process steps and identifying the most suitable methods for each step. Additionally, future research directions are suggested for potential enhancements to the MAMCA framework by integrating varied methodologies.

This paper proposes an interval hesitant fuzzy multi-criteria decision-making model based on improved projection measure, aiming to solve the non-standardization problem in traditional methods. By improving the projection measure and ensuring that its value is in the interval [0,1], the stability and accuracy of the decision results are improved. Compared with the existing methods, this method shows stronger robustness in multi-criteria decision-making, especially in complex decision-making scenarios. The effectiveness of the model is verified by example analysis, which provides a new theoretical tool for multi-criteria comprehensive decision-making.

Management of ecosystem services in mountain forests: Review of indicators and value functions for model based multi-criteria decision analysis

A comparative analysis of DEA as a discrete alternative multiple criteria decision tool

Real-time scheduling issues in Assembly Job Shops (AJS) have received little attention from researchers compared to regular job shops or flow shops. Simple Priority Rules (SPRs) are effective in generating job priorities in a shop floor environment by considering single criteria. Many real-world problems consider multiple criteria, where SPRs are not effective. This work aims to analyse the performance of TOPSIS-based Multi-Criteria Decision Making (MCDM) rules intending to minimize Makespan, Mean Flowtime, Mean Tardiness, and Maximum Tardiness of AJS. This study considers benchmark problem instances, which include flat, tall, and complex product structures, as well as large-scale real-world hybrid assembly job shop problems with realistic constraints for performance analysis. Proposed MCDMs are integrated with Discrete Event Simulation (DES) models for performance evaluation. The proposed TOPSIS-based MCDM method does better than the most popular priority dispatching rules (PDRs) in the literature on both large-scale benchmark instances and real-world assembly job shop problems. For the case study problem, the Makespan is improved by 24%, the Mean Flowtime is improved by 39%, and Tardiness is improved by 65% when compared against the best performing SPR. MCDM techniques integrated with discrete event simulation models offer a robust framework for handling the complexities of scheduling in static and dynamic situations. The proposed approach facilitates more effective and economical scheduling decisions by combining various criteria and adjusting to changing situations, which ultimately improves operational performance.

Roles of geospatial technology in eco-industrial park site selection: State–of–the-art review

Government agencies are responsible for making complex, high-stake decisions, which require them to balance political, technical, and economic considerations. Pressure from stakeholders and administrative requirements necessitate a traceable and transparent method for decision making. Multi-criteria decision analysis (MCDA) methods are available to decision makers to facilitate systematic treatment of the information and factors necessary to make informed and effective decisions in complex circumstances. A survey of gray and academic literature was conducted to gauge the level of application and awareness of MCDA methods by US government agencies and determine if the tools’ benefits are being realized. Results show an increase in awareness and consideration of MCDA from 2000 to the present, and that agencies are especially considering and using tools to engage with stakeholders. Government agencies would benefit from extending the application of MCDA to strategic planning and congressional engagement, as well as by standardizing MCDA use to better enable inter-agency collaboration and communication.

One of the most significant activities of life is transportation. An efficient transportation network has many health benefits on a society, such as making work and essential services, recreation facilities, and shopping centers accessible by people and allowing people to contact each other. However, the continuous increase in demand for transportation and consequently the use of vehicles using conventional fuel types, such as fossil fuels, causes serious problems on the environment. Alternative energy sources such as electricity, natural gas, propane, ethanol, methanol, biodiesel and hydrogen, some of which are similar with the traditional fuels and some of which require completely different vehicle properties, are considered as alternatives to gasoline and diesel fuels. As of today since there is a wide variety of vehicle options, including hybrid and electric vehicles, for users the decision on the type of vehicle to be preferred is certainly a challenging task for the purchasers. During the decision-making process, all options should be carefully evaluated in terms of advantages and disadvantages, where Multi Criteria Decision Making (MCDM) can be a helpful tool for decision-makers in this challenging process. In the present study, with the ultimate motivation of aiding the decision making process for renewing the shuttle bus fleet -that is currently composed of all internal combustion engine vehicles- serving to a university campus, we concentrate on the problem of selecting the most suitable vehicle for a medium-scale settlement's road network.

BackgroundThis study aimed to establish a suitable value assessment framework for orphan medicinal products in China based on the multi-criteria decision analysis (MCDA) method.MethodsFirst, a draft framework of the MCDA criteria was built based on a systematic literature evaluation and the EVIDEM framework tools. Second, stakeholder groups were formed and expert opinions were collected through the brainstorming and expert consultation methods. Third, from the perspective of stakeholders, the five-point weighting method and a two-step percentile distribution method were employed to weigh the quantitative criteria in the framework for orphan drug value evaluation. Meanwhile, from the public perspective, a survey was conducted on a sample of 71 people to obtain the scoring scale of the framework for orphan drugs through a two-step percentile distribution method. Finally, based on the synthetization and comparison of all evidence and methods, we developed the framework criteria and scoring scale for the orphan medicinal products.ResultsCombined with the stakeholder selection and suggestions in the stakeholder workshop, the framework criteria for the evaluation were constructed based on China’s national conditions, which included 11 quantitative and 8 qualitative criteria. The two-step percentile distribution method was selected as the weighting method.ConclusionsMCDA is feasible for the value assessment of orphan drugs in China and can be used as a supplementary tool for drug access decisions in medical insurance. It is suggested to further improve the value assessment framework of orphan medicinal products, scientifically evaluate the MCDA framework weighting method, explore a framework system suitable for China’s national conditions.

This article describes in detail how optimizing performance studies were measured on the selection of low global warming potential (GWP) refrigerants for automobile air conditioning to obey the environmental protocols with the multi-criteria decision-making (MCDM) tools. Among 14 alternatives, three different types of MCDM tools are used in this study, i.e., the technique for order of preference by similarity to ideal solution (TOPSIS) approach, evaluation based on distance from average solution (EDAS), and multi-objective optimization based on ratio analysis (MOORA) for time consumption. For the data processing, the thermodynamic characteristics, environmental friendliness, and economic circumstances are optimized with the multiple response attributes, including the latent heat of vaporization, thermal conductivity, vapor pressure, saturated fluid density, specific heat capacity, dynamic viscosity, GWP, ozone depletion potential, and cost per pound. From MCDM techniques, the grade values and weights assigned by decision-makers are standardized into a comparable measure. Among the 14 refrigerants, R430A has been applied foremost in EDAS, TOPSIS, and MOORA methods with the highest closeness coefficient values of 0.786, 0.701, and 0.064, respectively. R-744 was found to be the worst refrigerant by both EDAS and TOPSIS methods, while R1233zd (E) was found to be the worst refrigerant by the MOORA method.

Compression ignition engine performance modelling using hybrid MCDM techniques for the selection of optimum fish oil biodiesel blend at different injection timings