Search Results (12)

This paper contributes to queueing systems by introducing the concept of sustainable integral optimization, which integrates both quantitative and qualitative criteria, such as comfort, anxiety, and perceived service quality, into traditional performance metrics. We extend Kendall’s notation with a new element (G), focused on subjective sustainability indicators. The optimization process is conducted via the Integral Analysis Method (IAM), complemented by the SMAA framework for multicriteria decision-making. To demonstrate the applicability of the proposed approach, a case study in a high-end car dealership is developed. The goal is to address a persistent deficiency in queueing theory literature by incorporating human-centered sustainability principles, seeking a systemic balance between operational efficiency and user-oriented effectiveness in service delivery. Full article

An artificial intelligence procedure (AIP) model is presented to generate a robust multicriteria ranking for decision-making in problems with a large number of criteria, which jointly uses genetic algorithms, the OWA method, and SMAA. The main contribution of this AIP model is to reduce the cognitive effort of the decision-maker in determining the weights of the criteria involved in the decision problem, since, with the proposed model, these weights are inferred according to the decision-maker’s preferences, which can result in a ranking of the alternatives called a robust ranking. Robustness provides the expert with the certainty that, despite variations in their preferences and, therefore, in the weights inferred by the model, the presented robust ranking will not undergo significant changes, giving stability to the decision-making solution in a stable environment and reflecting the decision-maker’s preferences. This is one of the main contributions of applying the AIP model, unlike other models that do not provide a robust solution, as described in the application of the proposed AIP model to a multicriteria decision problem with many criteria, such as the state competitiveness analysis problem presented by the Mexican Institute for Competitiveness (IMCO). Full article

This paper presents a novel technique for extracting the alveolar part of human breath. Gas exchange occurs between blood and inhaled air in the alveoli, which is helpful in medical diagnostics based on breath analysis. Consequently, the alveolar portion of the exhaled air contains specific concentrations of endogenous EVOC (exogenous volatile organic compound), which, among other factors, depend on the person’s health condition. As this part of the breath enables the screening for diseases, accurate sample collection for testing is crucial. Inaccurate sampling can significantly alter the composition of the specimen, alter the concentration of EVOC (biomarkers) and adversely affect the diagnosis. Furthermore, the volume of alveolar air is minimal (usually <350 mL), especially in the case of people affected by respiratory system problems. For these reasons, precise sampling is a key factor in the effectiveness of medical diagnostic systems. A new technique ensuring high accuracy and repeatability is presented in the article. It is based on analyzing the changes in carbon dioxide concentration in human breath using a fast and compensated non-dispersive infrared (NDIR) sensor and the simple moving adjacent average (SMAA) algorithm. Research has shown that this method accurately identifies exhalation phases with an uncertainty as low as 20 ms. This provides around 350 ms of breath duration for carrying out additional stages of the diagnostic process using various types of analyzers. Full article

Large amounts of hydrochar have been produced during the last decade by various hydrothermal carbonisation (HTC) processes. While the products of HTC seem to have widespread acceptance as valuable and efficient materials with advantages in their energy and environmental applications, which include soil improvement, heavy metal recovery, and many more, a comprehensive framework for the assessment of the different hydrochars based on their characteristics is missing. In this study, a framework for the assessment of hydrochars is proposed with the utilisation of Multi-Criteria Decision-Aiding (MCDA) methodologies. A hierarchical structure of independent criteria is established on a comprehensive level including three lines of evidence (LoE), i.e., Environmental, Economic, and Social LoE, which further include the assessment criteria. Hierarchical-SMAA-PROMETHEE is proposed as the most suitable MCDA methodology to be applied for assessing hydrochars based on the proposed framework. A case study is performed to demonstrate the utility of the framework and the advantages it offers to analysts and decision-makers. Hierarchical-SMAA-PROMETHEE is a non-compensatory method that enables exploring the decision problem on more than one level (comprehensive vs. LoE) and includes robust recommendations on the preference model and the elicitation of weights. Full article

Mini-grids need to imitate the transition path of a traditional grid to maintain their position as a sustainable energy access alternative, while aligning with the objectives of the seventh Sustainable Development Goal. One such strategy is implementing smart-metering solutions to improve business viability and remote monitoring of distributed mini-grid assets. However, selecting smart meters presents a significant challenge for mini-grid operators, primarily due to the installation costs involved and the complexities associated with operating mini-grids in rural areas. Against this backdrop, the current case study’ demonstrates the utility of multi-criteria decision aids, such as stochastic multi-criteria acceptability analysis (SMAA), to assist mini-grid operators in making informed decisions concerning smart-meter selection. In addition, practitioners’ narratives elucidate how implementing smart metering can function as part of mini-grid operations in rural areas. Furthermore, narratives highlight the importance of considering context-specific conditions to avoid the under-utilisation of smart meters. Full article

Growth trends in passenger transport demand and gross domestic product have so far been similar. The increase in mobility in one area is connected with the increase in GDP in the same area. This increase is representative of the economic and social development of the area. At the same time, the increase in mobility produces one of the most negative environmental impacts, mainly determined by the growth of mobility of private cars. International attention is given to the possibilities of increasing mobility and, therefore, social and economic development without increasing environmental impacts. One of the most promising fields is that of MaaS: Mobility as a Service. MaaS arises from the interaction of new user behavioral models (demand) and new decision-making models on services (supply). Advanced interaction arises from the potentialities allowed by emerging ICT technologies. There is a delay in the advancement of transport system models that consider the updating of utility and choice for the user by means of updated information. The paper introduces sustainability as defined by Agenda 2030 with respect to urban passenger transport, then examines the role of ICT in the development of MaaS formalizing a dynamic model of demand–supply interaction explicating ICT. Finally, the advanced Sustainable MaaS, defined SMaaS, is analyzed, evidencing the contribution to achieving the goals of Agenda 2030. Full article

This study is about multicriteria decision aiding (MCDA) for the green airports program of the Moroccan Airport Authority ONDA. The goal of the program is to develop significant amounts of renewable power at airports. In particular, ONDA wants to select airports at which large solar and wind power parks should be built. Multiple criteria, including economy, technical feasibility, and environmental concerns, must be considered simultaneously. In this study, we apply Stochastic Multicriteria Acceptability Analysis (SMAA) for ranking the candidates to be developed into green airports. The analysis is conducted in phases with different sets of criteria. This study is the first application of MCDA for developing large-scale renewable energy production at airports. As a theoretical novelty, the pairwise winning indices of SMAA are used to form stochastic partial and complete rankings of the alternatives. Based on the results, two alternatives obtain the best and second-best rank in every model, and one alternative is always last, while the ranks of the remaining alternatives vary depending on the set of criteria. Full article

Passenger mobility plays an important role in today’s society and optimized transport services are a priority. In recent years, MaaS (Mobility as a Service) has been studied and tested as new integrated services for users. In this paper, MaaS is studied considering the sustainability objectives and goals to be achieved with particular reference to the consolidated methodologies adopted in the transport systems engineering for design, management, and monitoring of transport services; it is defined as Sustainable MaaS (S-MaaS). This paper considers the technological and communication platform essential and assumed to be a given considering that it has been proposed in many papers and it has been tested in some areas together with MaaS. Starting from the MaaS platform, the additional components and models necessary for the implementation of an S-MaaS are analyses in relation to: a Decision Support System (DSS) that supports MaaS public administrations and MaaS companies for the design of the service and demand management; a system for the evaluation of intervention policies; and also considers smart planning for a priori and a posteriori evaluation of sustainability objectives and targets. Full article

Online reviews of hotels reflect tourist perception and evaluation, which are becoming an important perspective of studying hotel selection. In this paper, we prefer to use a probabilistic linguistic term set (PLTS) to fully reveal evaluation grades and the corresponding probability distribution in the online reviews of hotels. In this way, we propose a novel stochastic dominance-based approach based on stochastic dominance degrees of PLTSs and a stochastic multi-criteria acceptability analysis (SMAA) method that tolerates missing information. Among them, first-, second-, and third-order stochastic dominance degrees of PLTSs are calculated on the premise that the dominance relationships between PLTSs can be defined based on first-, second-, and third-order stochastic dominance rules of PLTSs. Based on these basic researches, five hotels are selected as alternatives in our case study to verify the validity and feasibility of the proposed approach. In the end, data analysis illustrates the influence of parameter and linguistic scale functions and how to choose appropriate parameter values. Furthermore, comparative analysis with other methods shows the stability of the proposed approach. Full article

The imperative to reduce emissions to counteract climate change has led to the use of renewables progressively in more areas. Looking at district heating, there is a growing interest in coupling current production systems and carbon-neutral technologies. This paper presents a methodology to support decision making about carbon-neutral technologies for district heating. The process is organized in two stages, the first one aims at optimizing the different carbon-neutral technologies according to an objective function and assess uncertainties and dependencies. In the second stage, the alternatives are evaluated using Stochastic Multicriteria Acceptability Analysis (SMAA), a simulation-based method specifically designed to consider imprecise information. The methodology was applied to a case-study in Torino, Italy, which simulates the city district heating network at a smaller scale, with the aim to explore strategies for replacing gas boiler with more sustainable technologies. According to preference information provided by decision makers, the most preferred alternative resulted in the introduction of a solar heat plant combined with an increase size of daily heat storage. Solar heat can benefit from incentives while reducing operational costs and emissions, maximizing the use of carbon-neutral heat thanks to the storage. Full article

Uncertainty should be taken into account when establishing multiobjective task assignment models for multiple unmanned combat aerial vehicles (UCAVs) due to errors in the target information acquired by sensors, implicit preferences of the commander for operational objectives, and partially known weights of sensors. In this paper, we extend the stochastic multicriteria acceptability analysis-2 (SMAA-2) method and combine it with integer linear programming to achieve multiobjective task assignment for multi-UCAV under multiple uncertainties. We first represent the uncertain target information as normal distribution interval numbers so that the values of criteria (operational objectives) concerned can be computed based on the weighted arithmetic averaging operator. Thus, we obtain multiple criteria value matrices for each UCAV. Then, we propose a novel aggregation method to generate the final criteria value matrix based on which the holistic acceptability indices are computed by the extended SMAA-2 method. On this basis, we convert the task assignment model with uncertain parameters into an integer linear programming model without uncertainty so as to implement task assignment using the integer linear programming method. Finally, we conduct a case study and demonstrate the feasibility of the proposed method in solving the multiobjective task assignment problem multi-UCAV under multiple uncertainties. Full article

Combined heat and power (CHP) is a promising technology that can contribute to energy efficiency and environmental protection. More CHP-based energy systems are planned for the future. This makes the evaluation and selection of CHP systems very important. In this paper, 16 CHP units representing different technologies are taken into account for multicriteria evaluation with respect to the end users’ requirements. These CHP technologies cover a wide range of power outputs and fuel types. They are evaluated from the energy, economy and environment (3E) points of view, specifically including the criteria of efficiency, investment cost, electricity cost, heat cost, CO₂ production and footprint. Uncertainties and imprecision are common both in criteria measurements and weights, therefore the stochastic multicriteria acceptability analysis (SMAA) model is used in aiding this decision making problem. These uncertainties are treated better using a probability distribution function and Monte Carlo simulation in the model. Moreover, the idea of “feasible weight space (FWS)” which represents the union of all preference information from decision makers (DMs) is proposed. A complementary judgment matrix (CJM) is introduced to determine the FWS. It can be found that the idea of FWS plus CJM is well compatible with SMAA and thus make the evaluation reliable. Full article