Application of Topological Operators over Data from InterCriteria Analysis

In this paper, two topological operators T and U over intuitionistic fuzzy sets are considered and applied. As a case study a parameter identification problem of E. coli fed-batch cultivation process model using genetic algorithms is investigated. A new result regarding T and U is established. The results obtained by the application of the topological operators over data processed by InterCriteria Analysis are discussed

A spatial decision support system for the analysis of environmental impacts of integrated crop-livestock production system

Recent shifts toward intensive and large confined livestock production units to enhance economic growth coupled with increased concerns for air, soil, and water quality have necessitated the development of computer-based management decision support systems for selecting environmentally sound production sites and for planning sustainable production systems. This dissertation describes the development and application of an interactive spatial decision support system that integrates a geographic information system, spatial and biophysical modeling, and a knowledge-based system into an interactive tool to facilitate planning and management of environmentally-sound livestock production. The spatial decision support can be used to select suitable watershed land areas for siting livestock production, to select fields for manure application, and to determine the potential impacts of livestock production practices on ground and surface water quality. The site selection component of the spatial decision support system is based on the ARC/INFO geographic information system and incorporates the effects of land use, soil type, topography, proximity to roads and surface water bodies, and other aesthetic and political considerations as well as multicriteria analysis techniques. The groundwater quality modeling component of the decision support system integrates a geographic information system and water quality modeling, using training sets from NLEAP water quality modeling, to estimate nitrate leaching. In order to evaluate nutrient loading on surface water from integrated crop-livestock production a surface water quality model capable of incorporating the spatial dynamics of watershed was needed. The AGNPS distributed-parameter model was used for this purpose. The AGNPS model integrated with ARC/INFO GIS forms a user-friendly modeling interface for surface water quality analysis. The interface automates extraction of the input parameters from GIS data layers and allows the user to interactively generate scenarios of nutrient management practices in crop-livestock production. In order to demonstrate utility of the integrated system, example applications were performed on 7075-ha Lake Icaria watershed in southern Iowa

Multicriteria methodologies for the appraisal of smart grid projects when flexibility competes with grid expansion

The severe consequences expected due to the increased frequency and intensity of extreme weather events call for improving the environmental sustainability of our society. The electricity sector is pivotal in the path toward a climate-neutral society. Nowadays, the massive use of renewable energy sources requires that electricity demand follows energy production. Demand has to be flexible, as well as the renewable generation and the grid infrastructures. The power system has to assume a decentralised structure and integrate the transportation and cooling and heating sectors. All customers connected to the electrical grid have to contribute to the power system management and participate in the related markets. The power system has to become smart; all technical and market processes have to be digitalised to enable new functionalities and services. The power system transformation requires rethinking planning and operation practices to accommodate the changes and take advantage of the related opportunities. The novel features and services available in the active and flexible power system will influence the customers' daily habits; therefore, the impacts generated by planning initiatives will cross the power system borders by impacting society as a whole. Since the power system will be operated closer to its technical limits, it is crucial to enhance the management of uncertainties by the increased accuracy of load and generation forecast. This thesis addresses the ongoing power system transformation by focusing on the distribution system, which will face unprecedented changes. This thesis concerns novel approaches for appraising the project initiatives based on the use of the users' flexibility connected to the grid. Traditional appraisal tools are no longer effective; therefore, decision-makers have to be supported with tools capable of capturing the complexity of the future power system in which flexibility measures compete with grid expansion. In this thesis, an assessment framework for smart grid initiatives which combines the cost-benefit analysis and the multi-criteria analysis proposed. Based on international guidelines, this framework allows for a systematic and simultaneous assessment of tangible and the intangible impacts considering conflicting criteria. To complete the assessment framework, a novel methodology which combines Regret Theory and multi-criteria analysis is proposed. The proposed methodology represents one of the main contributions of this dissertation. It supports the decision-maker to identify the most valuable option by decomposing the complex decision-making problem of smart grid planning and rejecting personal biases by avoiding the need for defining the evaluation criteria relevance. However, the stakeholders’ perspective can be included in terms of constraints for the minimax optimisation problem. In conclusion, the contribution of the thesis is to provide decision-making support tools for strategical power system planning. The research activities described in this document have been aimed at supporting system operators and regulatory bodies by providing tools for smart grid project appraisal and improving the accuracy of power system studies considering the novel context features

A FRAMEWORK FOR STRATEGIC PROJECT ANALYSIS AND PRIORITIZATION

Projects that support the long-term strategic intent and alignment are considered strategic projects. Therefore, these projects must consider their alignment with the organization’s current strategy and focus on the risk, organizational capability, resources availability, political influence, and socio-cultural factors. Quantitative and qualitative methods prioritize the projects; however, they are usually suitable for specific industries. Although prioritization models are used in the private sector, the same in the public sector is not widely seen in the literature. The lack of models in the public sector has happened because of the projects’ social implications, the value perception of different projects in the public sector, and potentially differing value perceptions attached to the types of projects in different decision-making environments in the public sector. The thesis proposes a generic framework to develop a priority list of the available basket of projects and decide on projects for the next undertaking. The focus of the thesis is on public projects. The analysis in the framework considers the critical factors for prioritization obtained from the literature clustered through the agglomerative text clustering technique. In the proposed framework, 13 critical clusters are identified and weighted using the Criteria Importance Through Intercriteria Correlation (CRITIC) method to develop their ranking using the Technique for Order of Preference Similarity Ideal Solution (TOPSIS) method. In addition, the proposed framework uses vector weighting to prioritize projects across industries. The applicability of the framework is demonstrated through Qatar’s real estate and transportation projects. The outcome obtained from the framework is compared with those obtained through the experts using the System Usability Scale (SUS). The comparison shows that the framework provides good predictability of the projects for implementation

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

Collected Papers (on Physics, Artificial Intelligence, Health Issues, Decision Making, Economics, Statistics), Volume XI

This eleventh volume of Collected Papers includes 90 papers comprising 988 pages on Physics, Artificial Intelligence, Health Issues, Decision Making, Economics, Statistics, written between 2001-2022 by the author alone or in collaboration with the following 84 co-authors (alphabetically ordered) from 19 countries: Abhijit Saha, Abu Sufian, Jack Allen, Shahbaz Ali, Ali Safaa Sadiq, Aliya Fahmi, Atiqa Fakhar, Atiqa Firdous, Sukanto Bhattacharya, Robert N. Boyd, Victor Chang, Victor Christianto, V. Christy, Dao The Son, Debjit Dutta, Azeddine Elhassouny, Fazal Ghani, Fazli Amin, Anirudha Ghosha, Nasruddin Hassan, Hoang Viet Long, Jhulaneswar Baidya, Jin Kim, Jun Ye, Darjan Karabašević, Vasilios N. Katsikis, Ieva Meidutė-Kavaliauskienė, F. Kaymarm, Nour Eldeen M. Khalifa, Madad Khan, Qaisar Khan, M. Khoshnevisan, Kifayat Ullah,, Volodymyr Krasnoholovets, Mukesh Kumar, Le Hoang Son, Luong Thi Hong Lan, Tahir Mahmood, Mahmoud Ismail, Mohamed Abdel-Basset, Siti Nurul Fitriah Mohamad, Mohamed Loey, Mai Mohamed, K. Mohana, Kalyan Mondal, Muhammad Gulfam, Muhammad Khalid Mahmood, Muhammad Jamil, Muhammad Yaqub Khan, Muhammad Riaz, Nguyen Dinh Hoa, Cu Nguyen Giap, Nguyen Tho Thong, Peide Liu, Pham Huy Thong, Gabrijela Popović‬‬‬‬‬‬‬‬‬‬, Surapati Pramanik, Dmitri Rabounski, Roslan Hasni, Rumi Roy, Tapan Kumar Roy, Said Broumi, Saleem Abdullah, Muzafer Saračević, Ganeshsree Selvachandran, Shariful Alam, Shyamal Dalapati, Housila P. Singh, R. Singh, Rajesh Singh, Predrag S. Stanimirović, Kasan Susilo, Dragiša Stanujkić, Alexandra Şandru, Ovidiu Ilie Şandru, Zenonas Turskis, Yunita Umniyati, Alptekin Ulutaș, Maikel Yelandi Leyva Vázquez, Binyamin Yusoff, Edmundas Kazimieras Zavadskas, Zhao Loon Wang.‬‬‬

Symmetric and Asymmetric Data in Solution Models

This book is a Printed Edition of the Special Issue that covers research on symmetric and asymmetric data that occur in real-life problems. We invited authors to submit their theoretical or experimental research to present engineering and economic problem solution models that deal with symmetry or asymmetry of different data types. The Special Issue gained interest in the research community and received many submissions. After rigorous scientific evaluation by editors and reviewers, seventeen papers were accepted and published. The authors proposed different solution models, mainly covering uncertain data in multicriteria decision-making (MCDM) problems as complex tools to balance the symmetry between goals, risks, and constraints to cope with the complicated problems in engineering or management. Therefore, we invite researchers interested in the topics to read the papers provided in the book

Multiple Criteria Decision Support; Proceedings of an International Workshop, Helsinki, Finland, August 7-11, 1989

Multiple Criteria Decision Making has been an important and active research area for some 20 years. In the 1970's, research focused on the theory of multiple objective mathematical programming and on procedures for solving multiple objective mathematical programming problems. During the 1980's, a shift in emphasis towards multiple criteria decision support was observed. Accordingly, much research has focused on the user interface, the behavioral foundations of decision making, and on supporting the entire decision-making process from problem structuring to solution implementation. Because of the shift in research emphasis the authors decided to make "Multiple Criteria Decision Support" the theme for the International Workshop, which was held at Suomen Saeaestoepankkiopisto in Espoo, Finland. The Workshop was organized by the Helsinki School of Economics, and sponsored by the Helsinki School of Economics and IIASA, Austria. This volume provides an up-to-date coverage of the theory and practice of multiple criteria decision support. The authors trust that it will serve the research community as well as the previously published Conference Proceedings based on IIASA Workshops