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The key elements, or pillars, of food security are stated as food availability, food access, food utilization, and stability. These food security pillars are often linked to food security interventions at the national, community or household level. However, if the urban 'household' is the unit of interest for any food security intervention, this research asks if a more holistic element, or pillar, is needed. The aim of this research has been to explore the socio-economic aspects of food security/insecurity that we have termed as a result of the research "food acquirability". Through the use of structured questionnaires (n = 120), and analysis of the data derived from local market and supermarket settings in the city of Awka, Nigeria, the concept of food acquirability has emerged and been conceptualized and critiqued. The contribution of this paper is to frame the concept of acquirability with regard to food security in Nigeria in order to develop a better understanding of the factors that impact household urban food security/insecurity and how they can be effectively mitigated. Factors of acquirability that emerged were culture, time poverty, resource availability and cooking skills, and household food preference and meal choice. [ABSTRACT FROM AUTHOR]

Research objectives so that the quality of decisions made by leaders in the organization can be measured using valid and reliable measurement tools measured by using valid and reliable measuring instruments. Method literature review, questionnaire formulation, validity & reliability test validity & reliability of the questionnaire. Results The questionnaire is valid and reliable to be used as a measuring tool for Decision Quality. Contribution this study aims to provide a research instrument that is to measure Decision Quality. The quality of the decision is the quality that results from the results of the decision that has been applied or tested to the maximum and the results are seen to the maximum and assessed to the maximum as well. From the results of data processing using SPSS, it produces a Scale Statistics Mean of 46.8829, Variance 41.133, Std Deviation 6.41352, Validity respondent 205, Crochbach Alpa 0.888. Product Moment Correlation coefficient or rcount > 0.3, so it can be said that all statement items on the questionnaire have good validity. Meanwhile, the entire Cronbach's Alpha coefficient value obtained for all items is > 0.872 so it can be stated that all statement items on the questionnaire have good reliability (> 0.6). [ABSTRACT FROM AUTHOR]

In this study a real world industrial MPS problem is addressed using the SMF approach. A decision maker, analyst and implementer, all play significant roles in making judgements in an uncertain environment, which is where this difficulty arises in the chocolate manufacturing business. As analysts our goal is to identify a solution with a higher LOS that will enable the decision maker to reach a conclusion. Because all the coefficients including the goals, technical and resource factors are well defined. The MPS problem is taken into consideration. With 24 constraints and 6 variables, this is regarded as one of the sufficiently large problem, which LOV is appropriate for getting satisfactory OR can be determined by a decision maker. To increase the satisfactory income, the decision maker can also advice to the analyst some feasible modification to FI. This collaborative process between the analyst, decision maker and implementer must continue until the best possible solution is found and put into action. [ABSTRACT FROM AUTHOR]

Currently, most existing cryptocurrency exchanges do not have tools in their arsenal that would allow them to verify and investigate information disseminated on social media regarding a particular cryptocurrency. This allows to conduct research with the subsequent development of an appropriate tool that, if used correctly, will provide users with recommendations on how to proceed with the cryptocurrency under investigation. Based on this advice, interested parties will be able to adjust their decisions regarding further financial steps. As part of this task, it is important to choose a social network that would best meet the requirements, as this is what determines the impact of celebrity publications on the formation of prices for a particular cryptocurrency at a certain point in time. The importance and existence of this influence has been previously proven by statistical methods. The purpose of the study is to identify and analyse the key aspects when choosing social networks for further monitoring of social groups in order to analyse the impact of posts on the course of the chosen cryptocurrency. The object of the study is social networks. A set of selection criteria, coefficients of their importance, and statistical data on the selected social networks were used as input data, on the basis of which the values of the alternatives (social networks) will be obtained. The objective of the study is to evaluate and rank social networks in order to choose the one that will best meet the specifics of analysing the impact of social media posts on the cryptocurrency rate. Research methods. The ranking of social networks was carried out by the value of the value function of alternatives, calculated using the linear convolution method. Results. As a result of the research, an algorithm has been developed that allows analysing the selected social networks for their compliance with the formulated criteria. The results of the experiment with the selected social networks were presented. As a result, a ranked list of them is obtained. Based on the results obtained, the authors will develop an information technology for determining the impact of posts of famous people in social networks on cryptocurrency rates.

Due to rapid economic growth, the demand for transportation has escalated, with cars and motorcycles being the most common personal vehicles. However, motorcycles have gained favor as a mode of transportation due to their ease of maneuvering through traffic, cost-effectiveness, and lower fuel consumption. Presently, there is a multitude of motorcycle manufacturers offering a diverse array of options. This study is focused on ascertaining the top motorcycle brand based on well-defined criteria, employing the fuzzy Technique for Order Preference by Similarity to Ideal Situation (fuzzy TOPSIS). Three expert decision makers were provided with a questionnaire to rank three motorcycle brands commonly used in Malaysia based on specific criteria: price, safety, efficiency, design, performance, and durability. Computational analyses were conducted, revealing Yamaha as the top-ranked brand with a closeness coefficient (CC) value of 0.2869, closely trailed by Honda with a CC of 0.2852. Modenas, on the other hand, ranked the lowest among the brands analyzed, with a CC of 0.1447. The marginal difference of 0.017 in CC between Yamaha and Honda suggests the highly competitive scenario between these two brands. By providing a comprehensive assessment of motorcycle brands, this study seeks to layout information of consumer preferences in decision making for motorcycle purchases. The preliminary results served as aid for manufacturers or retailers of the motorcycle market.

The Flexible Job Shop Scheduling Problem (FJSP) emerges as a challenging extension of the classic Job Shop, presenting NP-Hard characteristics. In the FJSP, a set of jobs, comprising multiple operations, must be allocated to a predefined set of machines, each with its respective execution times. The distribution of operations across machines significantly impacts scheduling efficiency, which can be evaluated and optimized based on various performance criteria and objectives. To address this complex problem, a multi-objective optimization algorithm is employed, focusing on three main performance criteria: completion time of all operations (Makespan), load assigned to the most heavily utilized machine, and the sum of loads across all machines. An FJSP algorithm based on the Artificial Bee Colony (ABC) metaheuristic (FJSP. ABC) generates a Pareto set comprising non-dominated and dominated solutions. These solutions represent optimal or near-optimal production schedules and offer diverse representations, such as Gantt charts. However, the decision-making process for selecting the best production schedule from the Pareto set demands additional considerations. To this end, we propose adopting a decision-making (DM) algorithm based on Fuzzy TOPSIS (Technique for Order of Preference by Similarity to the Ideal Solution in a Fuzzy environment). The DM Fuzzy TOPSIS algorithm accommodates the inclusion of variables not covered by the FJSP algorithm and aids decision-makers in identifying the most suitable production schedule based on the specific requirements of the production system. These additional variables may include maximizing or minimizing machine idleness, balancing the load of operations on machines, etc. Experimental results demonstrate that the application of the proposed algorithm yields values close to the expected outcomes for the analyzed variables proposed. The DM Fuzzy TOPSIS algorithm proves to be a valuable tool for supporting decision-making in production systems, assisting in the selection of the best production schedule among the optimal or near-optimal solutions obtained from the Pareto set. By integrating multi-objective optimization and decision-making techniques, this research contributes to more efficient and informed production scheduling practices, ultimately enhancing overall system performance.

The key elements, or pillars, of food security are stated as food availability, food access, food utilization, and stability. These food security pillars are often linked to food security interventions at the national, community or household level. However, if the urban ‘household’ is the unit of interest for any food security intervention, this research asks if a more holistic element, or pillar, is needed. The aim of this research has been to explore the socio-economic aspects of food security/insecurity that we have termed as a result of the research “food acquirability”. Through the use of structured questionnaires (n = 120), and analysis of the data derived from local market and supermarket settings in the city of Awka, Nigeria, the concept of food acquirability has emerged and been conceptualized and critiqued. The contribution of this paper is to frame the concept of acquirability with regard to food security in Nigeria in order to develop a better understanding of the factors that impact household urban food security/insecurity and how they can be effectively mitigated. Factors of acquirability that emerged were culture, time poverty, resource availability and cooking skills, and household food preference and meal choice.

Decentralization requires the bureaucracy to be able to solve various problems faced by the community at the local level. Meanwhile, the context of social change in society is directly proportional to the complexity of opportunities. The greater the complexity of the opportunity, the greater the uncertainty. The VUCA Era created uncertainty in human civilization, including public administration. Public administration must ensure how far the uncertainties in the VUCA Era can be anticipated in efforts to organize public administration, particularly in the decision-making process. For this reason, this article aims to identify the spirit of change in decision-making bureaucrats in Banyumas Regency to face the VUCA Era. The method used is a descriptive quantitative approach. Data was collected using a survey method for decision-making bureaucrats within government agencies in Banyumas Regency. The results of the study show that the level of spirit of change in decision-maker bureaucrats in Banyumas Regency in facing challenges in the VUCA era is at a moderate level. This indicates that decision-making bureaucrats still need support and encouragement in facing challenges in the VUCA era, especially adaptability and sustainable positive change.

The decision-making process is part of everyday life for people and organizations. When modeling the solutions to problems, just as important as the choice of criteria and alternatives is the definition of the weights of the criteria. This study will present a new hybrid method for weighting criteria. The technique combines the ENTROPY and CRITIC methods with the PROMETHE method to create EC-PROMETHEE. The innovation consists of using a weight range per criterion. The construction of a weight range per criterion preserves the characteristics of each technique. Each weight range includes lower and upper limits, which combine to generate random numbers, producing "t" sets of weights per criterion, allowing "t" final rankings to be obtained. The alternatives receive a value corresponding to their position with each ranking generated. At the end of the process, they are ranked in descending order, thus obtaining the final ranking. The method was applied to the decision support problem of choosing policing strategies to reduce crime. The model used a decision matrix with twenty criteria and fourteen alternatives evaluated in seven different scenarios. The results obtained after 10,000 iterations proved consistent, allowing the decision maker to see how each alternative behaved according to the weights used. The practical implication observed concerning traditional models, where a single final ranking is generated for a single set of weights, is the reversal of positions after "t" iterations compared to a single iteration. The method allows managers to make decisions with reduced uncertainty, improving the quality of their decisions. In future research, we propose creating a web tool to make this method easier to use, and propose other tools are produced in Python and R. [ABSTRACT FROM AUTHOR]

Introduction: Successful shared decision-making for critically ill intensive care unit (ICU) patients requires bidirectional communication. Through observation of ICU conversations, our study aimed to identify communication skill deficiencies in providers who care for patients in the ICU. Methods: This was an observational prospective study performed in a single urban academic medical center (671 beds) from June 2021 through August 2021. Twenty-three providers were recruited from medical and surgical ICU services (56 beds). Thirty-nine surrogate decision makers were identified. Provider skills were assessed using a customized observational tool that examined nonverbal communication, verbal communication, opening the discussion, gathering information, understanding the family's perspective, sharing information, reaching agreements on problems and plans, and providing closure. Results: Thirty-nine conversations were observed for six attending physicians, four fellow physicians, eight resident physicians, two nurse practitioners, and three physician assistants during the coronavirus 19 (COVID19) pandemic. A dedicated critical care provider engaged in 19 observed conversations; 20 discussions occurred with individuals rotating/consulting in the ICU. Communication skill did not depend on experience or area of expertise. Less than half of conversations achieved bidirectional communication proficiency. Scheduled conversations (n = 14) had significantly higher average communication scores than unscheduled encounters (n = 25). Conclusions: Superficial unidirectional communication with decision makers was commonly observed. Providers were less proficient at advanced communication skills needed for shared decision-making. We recommend that providers have more scheduled conversations, which were more productive in achieving bidirectional communication. A targeted simulation curriculum addressing these areas may improve patient, decision maker, and provider satisfaction, while promoting patient-centered care. [ABSTRACT FROM AUTHOR]

This paper presents the rationale for the relevance of decision support in the logistics of naval forces. A conceptual model of the naval logistics management system hierarchy and the transformation of unstructured information into structured data are discussed. The paper describes the conceptual model of a logistic information intelligent system for support of naval logistics decisions, the requirements for the model's hardware and software, and the results of ontological modeling and decomposition of management problems. [ABSTRACT FROM AUTHOR]

Problems arise when a lawfully appointed surrogate decision-maker wishes to decide on a course of action on behalf of a mentally incompetent patient that is against the patient’s best interests. This may arise: (i) where there is no advance directive, and the decision is made by the surrogate decision-maker on religious grounds; (ii) where the medical practitioners are of the opinion that the surrogate decision-maker’s decision is not in the best interests of the patient; (iii) where the close relatives of the patient do not agree with the decision by the surrogate decision-maker; and (iv) where the surrogate decision-maker asks the medical practitioners to undertake treatment or a procedure on the patient that is unlawful or unethical. Suggestions are made regarding what doctors should do when faced with each of these situations.

Many technological systems are characterized by fuzzy initial information, necessary for the development of their models, optimization and control of operating modes. Therefore, the purpose of this study is to formulate decision making problems for optimizing and controlling operating modes of such systems in a fuzzy environment and to develop methods for solving them. The developed heuristic methods of fuzzy multi-criteria decision making are based on the modification and combination of different principles of optimality. The proposed methods based on system models, knowledge and experience of the decision maker allow iterative improvement and effective decision making. On the basis of experimental–statistical methods, methods of expert evaluation, statistical and fuzzy models of the stabilization column have been developed. The conditions for judging the fuzzy model's effectiveness are determined and investigated. Using the proposed heuristic method based on the main criterion and maximin, the problem of two-criterion optimization of the stabilization column parameters in a fuzzy environment is solved. The results obtained confirm the advantages of the proposed method of fuzzy decision making in comparison with the results of known methods. The developed heuristic methods differ from known ones because they allow making adequate decisions in a fuzzy environment by maximizing the use of the collected fuzzy information. [ABSTRACT FROM AUTHOR]

The paper studies the problems of developing interconnected models of aggregates of complex chemical-technological systems (CTS) in conditions of scarcity and fuzziness of the initial information. Since the known methods of model development do not allow for solving these problems, we propose a systematic method that allows the development of a package of models of interconnected aggregates of complex CTS using the available information of a different nature. In the proposed method, formal and informal methods of system analysis are jointly used. Due to synergy and emergence, the proposed system allows the synthesis of the most adequate and effective CTS models using the knowledge, experience, and intuition of experts and other available data. Using the method, we have developed a package of models of interconnected reactors and used it in a case study for a reforming reactor and furnace of the Atyrau refinery catalytic reformer based on available statistical and fuzzy information. To study and optimize the operating modes of the reformer unit, a system of computer simulation and optimization of the reformer unit was created. Comparison of the obtained results of computer modeling and optimization with the results of known deterministic models shows the advantages of the proposed approach in the face of scarcity and fuzziness of the initial information. The importance and novelty of the proposed method lie in the possibility of developing a package of models of interrelated CTS units based on various types of available information. This allows one to systematically simulate and optimize the operating modes of the CTS. The practical significance of the results is that this case study can be successfully applied in the development of models of various technological units for oil refining, petrochemistry, and other industries.

Currently, active developments are underway to implement human and production resource management standards, new management mechanisms are emerging and being supplemented, but first of all, management activities can be assessed by the management decisions taken by the decision-maker, and the results that this management decision has brought. The relevance of the chosen topic is due to the fact that at present and in previous years there has been an increase in some independent variables, so management decisions at enterprises and other organisations are becoming more difficult and require taking into account larger criteria than usual. Therefore, the choice or development of a competent methodology for the management decision-making process would help the decision-maker not only to choose the most effective management decision, but also to minimise possible financial, social and other risks. The groups of factors that have a significant impact on the process of developing management solutions have been identified. The authors propose a step-by-step methodology for assessing the effectiveness level of the management decision-making and implementation mechanism. An updated version of the structural content of the methodological components necessary for the development of management solutions is proposed.

Artificial intelligence algorithms, particularly machine learning, are used to effectively support autonomous flight decisions based on satellite navigation signals. These algorithms can learn to recognize various patterns in navigation data and use them to make decisions on flight direction, speed, and other parameters. In any case, a combination of various technologies such as artificial intelligence algorithms, navigation systems, sensors, and other tools is necessary to effectively support autonomous flight decisions based on satellite navigation signals. The article presents the results of research on GPS signal jamming for UAVs and proposes a method to protect against such attacks using an ELECTRE-based algorithm that analyzes jamming signals. [ABSTRACT FROM AUTHOR]

Objective: The present study aims to estimate the public cost of depression in Romania during a seven-year time span to complement existing papers with data from Central and Eastern Europe and to identify and propose measures that allow efficient use of funds. Methods: We used data collected from the National Health Insurance System to analyze the main components of the cost. Findings: Indirect costs exceed direct costs. Within the direct costs, hospitalization and medicines still have an important share but are decreasing due to the intervention of outpatient services such as psychiatrists and psychotherapists. Conclusion: Since the goal is mental health, it is necessary to act early and quickly to decrease the burden in the long run. Annually, the mean direct cost of depression per patient is EUR 143 (part of it is represented by hospitalization, i.e., EUR 67, and psychotherapy, i.e., EUR 5), the mean cost of sick leaves per patient is EUR 273, and the total cost per patient is EUR 5553. Indirect costs (cost of disability and lost productive years) represent 97.17% of the total cost. An integrated approach to early diagnosis, effective treatment, monitoring, and prevention as well as included economic and social programs are needed to optimize indirect costs. [ABSTRACT FROM AUTHOR]

Conservation practitioners, natural resource managers, and environmental stewards often seek out scientific contributions to inform decision‐making. This body of science only becomes actionable when motivated by decision makers considering alternative courses of action. Many in the science community equate addressing stakeholder science needs with delivering actionable science. However, not all efforts to address science needs deliver actionable science, suggesting that the synonymous use of these two constructs (delivering actionable science and addressing science needs) is not trivial. This can be the case when such needs are conveyed by people who neglect decision makers responsible for articulating a priority management concern and for specifying how the anticipated scientific information will aid the decision‐making process. We argue that the actors responsible for articulating these science needs and the process used to identify them are decisive factors in the ability to deliver actionable science, stressing the importance of examining the provenance and the determination of science needs. Guided by a desire to enhance communication and cross‐literacy between scientists and decision makers, we identified categories of actors who may inappropriately declare science needs (e.g., applied scientists with and without regulatory affiliation, external influencers, reluctant decision makers, agents in place of decision makers, and boundary organization representatives). We also emphasize the importance of, and general approach to, undertaking needs assessments or gap analyses as a means to identify priority science needs. We conclude that basic stipulations to legitimize actionable science, such as the declaration of decisions of interest that motivate science needs and using a robust process to identify priority information gaps, are not always satisfied and require verification. To alleviate these shortcomings, we formulated practical suggestions for consideration by applied scientists, decision makers, research funding entities, and boundary organizations to help foster conditions that lead to science output being truly actionable. [ABSTRACT FROM AUTHOR]

Technological objects and processes are often characterized by fuzzy initial information necessary for developing their models and optimization. The purpose of the study is to develop a method for synthesizing linguistic models of fuzzy described objects and a heuristic method for solving the multicriteria optimization problem in a fuzzy environment. Based on the expert assessments and logical rules of conditional inference, a method for synthesizing linguistic models was developed for describing processes with fuzzy input and output parameters. To solve the problem of multicriteria optimization, a heuristic method based on the modification and combination of various optimality principles is proposed. Coking reactor models were developed by modifying the successive regression inclusion method and the least squares method. Linguistic models of the delayed coking process were developed in the Fuzzy Logic Toolbox, allowing to evaluate the coke quality depending on the temperature and pressure of coking reactors. Using the proposed heuristic method, the problem of two-criteria optimization of the delayed coking process with fuzzy constraints is solved. The results confirm the advantages of the proposed fuzzy approach compared with the well-known approaches. Unlike them, the proposed method allows making adequate decisions in a fuzzy environment by maximizing the use of available fuzzy information. [ABSTRACT FROM AUTHOR]

Aim. The article presents a qualitative analysis of a decision-maker - a criminal who broke the law against health and life, including a penitentiary repeat offender and a person convicted for the first time. The data presented concerns: motives for action, emotions in the decision-making process, self-assessment, knowledge from a criminal career, as well as plans for the future. Research methods. The article is based on the results of a qualitative analysis of 22 in-depth interviews with elements of a narrative interview. Results. According to the research, criminals who broke the law against health and life manifested economic and emotional motives, with emotional motives prevailing. The narratives contained fragments of statements that testified to cognitive distortions. The results of research on emotions appearing in the process of making a criminal decision indicate that the respondents experienced pleasant and unpleasant emotions. However, in this research group, positive emotions dominated, which were usually accompanied by emotional arousal. Emotions in the recognition of the subjects played an important role in their crime, and were assessed as a factor that limited their rational action. The respondents had knowledge of crime from their own experience, self-education and experiences gained from criminal friends. The respondents presented various plans for the future, which concerned both professional and private life. Conclusions. In their own narratives, the subjects showed cognitive distortions. Therefore, corrective work should focus on those distortions. An effective solution in the case of criminals against health and life could be social rehabilitation taking into account elements of cognitive-behavioral therapy. Due to the fact that the respondents assessed the role of emotions in committing crimes as significant, work on emotions should also be an important element of corrective work. [ABSTRACT FROM AUTHOR]

The decision-making process is part of everyday life for people and organizations. When modeling the solutions to problems, just as important as the choice of criteria and alternatives is the definition of the weights of the criteria. This study will present a new hybrid method for weighting criteria. The technique combines the ENTROPY and CRITIC methods with the PROMETHE method to create EC-PROMETHEE. The innovation consists of using a weight range per criterion. The construction of a weight range per criterion preserves the characteristics of each technique. Each weight range includes lower and upper limits, which combine to generate random numbers, producing “t” sets of weights per criterion, allowing “t” final rankings to be obtained. The alternatives receive a value corresponding to their position with each ranking generated. At the end of the process, they are ranked in descending order, thus obtaining the final ranking. The method was applied to the decision support problem of choosing policing strategies to reduce crime. The model used a decision matrix with twenty criteria and fourteen alternatives evaluated in seven different scenarios. The results obtained after 10,000 iterations proved consistent, allowing the decision maker to see how each alternative behaved according to the weights used. The practical implication observed concerning traditional models, where a single final ranking is generated for a single set of weights, is the reversal of positions after “t” iterations compared to a single iteration. The method allows managers to make decisions with reduced uncertainty, improving the quality of their decisions. In future research, we propose creating a web tool to make this method easier to use, and propose other tools are produced in Python and R.

In this work, we present a scheduling mechanism for deadline sensitive task or lease. It is very impelling and challenging to allocate on-demand resources within the deadline rather than rejecting the lease. The work studies the insight of existing backfilling algorithm that is used to schedule deadline sensitive lease in the Open Nebula cloud platform. In backfilling mechanism a lease is selected in First Come First Serve (FCFS) to be backfilled in which some ideal resources can be found out and allocated to other leases. Mainly, the scheduling performance of backfilling algorithm could be better when there are conflicts among the similar leases to backfill. Moreover, backfilling algorithm doesn’t allow to schedule a new deadline sensitive task during execution. The proposed work addresses such types of issues and improves the scheduling performances with respect to maximize the task acceptance ratio and reduce the task rejection ratio. Finally, the performances are compared with the existing mechanisms that are quite good.

Many cities around the world face the flooding management problems as extreme rainfall events have become more frequent. It’s of great practical significance to design an effective urban drainage system (UDS) to improve the stormwater runoff quality. An integrated decision-making analysis framework based on many-objective brain storm optimization is proposed to make the optimal design of UDS. Firstly, a generic mathematical model is presented considering five objectives simultaneously. Secondly, an effective many-objective brain storm optimization based on local region dominance is designed as the solver of the model and a set of Pareto-optimal solutions are obtained. Thirdly, two kinds of multi-attribute decision analysis methods are introduced to rank the Pareto-optimal solutions. Fourthly, the comparison experiments of a case study with three multi-objective swarm intelligence algorithms show the promising performance of the integrated decision-making framework and the corresponding optimization algorithm.

The issue of the Construction Council law is one of the most important laws due to the difficult reality that the various sectors of the Iraqi state suffer, and the government's ability to absorb the challenges of the development process, in light of the differences that are increasingly complex and intertwined every day about the nature of the parties that will contribute to the process of construction and reconstruction and providing services to the people rising up against bad performance The political class of the wise class, accompanied by a lack of confidence in any measure or law that the government offers to the people, this law remains dependent on the actual ability to resolve the outstanding issues related to services, improve them, provide a safe environment for investors, return the areas devastated by terrorism and create job opportunities for the youth and the unemployed. [ABSTRACT FROM AUTHOR]

Many technological systems are characterized by fuzzy initial information, necessary for the development of their models, optimization and control of operating modes. Therefore, the purpose of this study is to formulate decision making problems for optimizing and controlling operating modes of such systems in a fuzzy environment and to develop methods for solving them. The developed heuristic methods of fuzzy multi-criteria decision making are based on the modification and combination of different principles of optimality. The proposed methods based on system models, knowledge and experience of the decision maker allow iterative improvement and effective decision making. On the basis of experimental–statistical methods, methods of expert evaluation, statistical and fuzzy models of the stabilization column have been developed. The conditions for judging the fuzzy model’s effectiveness are determined and investigated. Using the proposed heuristic method based on the main criterion and maximin, the problem of two-criterion optimization of the stabilization column parameters in a fuzzy environment is solved. The results obtained confirm the advantages of the proposed method of fuzzy decision making in comparison with the results of known methods. The developed heuristic methods differ from known ones because they allow making adequate decisions in a fuzzy environment by maximizing the use of the collected fuzzy information.

Planning problems in healthcare systems have received greater attention in the last decade, especially because of the concerns recently raised about the scattering of surgical interventions among a wide number of different facilities that can undermine the quality of the outcome due to the volume-outcome association. In this paper, an approach to plan the amount of surgical interventions that a facility has to perform to assure a low adjusted mortality rate is proposed. The approach explicitly takes into account the existing interaction among patients' choices and decision makers' planning decisions. The first objective of the proposed approach is to find a solution able to reach quality in health outcomes and patients' adherence. The second objective is to investigate the difference among solutions that are identified as optimal by either only one of the actors' perspective, i.e., decision makers and patients, or by considering both the perspectives simultaneously. Following these objectives, the proposed approach is applied to a case study on Italian colon cancer interventions performed in 2014. Results confirm a variation in the hospital planned volumes when considering patients' behaviour together with the policy maker plan, especially due to personal preferences and lack of information about hospital quality. [ABSTRACT FROM AUTHOR]

For over last 20 years, significant changes have been observed in the age structure of the world’s population. The percentage of working-age population is steadily decreasing all over the world, and a relative number of retired people is increasing. It confirms that our society is ageing. Moreover, according to the United Nations population forecast the situation will get worse. The increasing number of seniors is also connected with the need to provide them with institutional support in the form of care. One of the key elements of helping older adults may be gerontechnology – an interdisciplinary field of research that uses technology to implement the aspirations and abilities of seniors. On the basis of a meticulous literature review, 9 groups of gerontechnology have been identified that have been rated with respect to 30 criteria. In the period December 2019 – January 2020 a representative sample of 1.152 Poles aged over 40 (acting as decision makers) took part in the research consisting of completing the prepared questionnaire. Based on selected Multiple Criteria Group Decision Making methods, linear ordering of gerontechnologies was prepared and the most preferred by respondents participating in the study was indicated.

Objective: The present study aims to estimate the public cost of depression in Romania during a seven-year time span to complement existing papers with data from Central and Eastern Europe and to identify and propose measures that allow efficient use of funds. Methods: We used data collected from the National Health Insurance System to analyze the main components of the cost. Findings: Indirect costs exceed direct costs. Within the direct costs, hospitalization and medicines still have an important share but are decreasing due to the intervention of outpatient services such as psychiatrists and psychotherapists. Conclusion: Since the goal is mental health, it is necessary to act early and quickly to decrease the burden in the long run. Annually, the mean direct cost of depression per patient is EUR 143 (part of it is represented by hospitalization, i.e., EUR 67, and psychotherapy, i.e., EUR 5), the mean cost of sick leaves per patient is EUR 273, and the total cost per patient is EUR 5553. Indirect costs (cost of disability and lost productive years) represent 97.17% of the total cost. An integrated approach to early diagnosis, effective treatment, monitoring, and prevention as well as included economic and social programs are needed to optimize indirect costs.

Satisfaction is relevant for decision makers (DM, Decision Makers). Satisfaction is the feeling produced in individuals by executing actions to satisfy their needs, for example, the payment of debts, jobs, or academic achievements, and the acquisition of goods or services. In the satisfaction literature, some theories model the satisfaction of individuals from job and customer approaches. However, considering personality elements to influence satisfaction and define preferences in strategies that optimize decision making provides the unique characteristics of a DM. These characteristics favor the scope of solutions closer to the satisfaction expectation. Satisfaction theories do not include specific elements of personality and preferences, so integrating these elements will offer more efficient decisions in computable models. In this work, a model of satisfaction with personality characteristics that influence the preferences of a DM is proposed. The proposed model is integrated into a preference-based optimizer that improves the decision-making process of a Virtual Decision Maker (VDM) in an optimization context. The optimization context addressed in this work is the product selection process within a food product shopping problem. An experimental design is proposed that compares two configurations that represent the cognitive part of an agent's decision process to validate the operation of the proposed model in the context of optimization: (1) satisfaction, personality, and preferences, and (2) personality and preferences. The results show that considering satisfaction and personality in combination with preferences provides solutions closer to the interests of an individual, reflecting a more realistic behavior. Furthermore, this work demonstrates that it is possible to create a configurable model that allows adapting to different aptitudes and reflecting them in a computable model. [ABSTRACT FROM AUTHOR]