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Article
Computer Science, Artificial Intelligence
Xu Yang et al.
Summary: This article proposes a fuzzy decision variables framework for large-scale multiobjective optimization. The framework divides the evolutionary process into fuzzy evolution and precise evolution stages. Fuzzy evolution blurs the decision variables to reduce the search range in the decision space for quick convergence, while precise evolution directly optimizes the actual decision variables to increase population diversity. Experimental results demonstrate that this framework significantly improves the performance and computational efficiency of multiobjective optimization algorithms in large-scale problems.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2023)
Article
Computer Science, Interdisciplinary Applications
Leonid Mylnikov
Summary: The paper addresses the timely problem of improving planning and management efficiency of production systems in the face of new innovation products. By formalizing processes and specifying project requirements, the paper shows that cost-inefficient project combinations can be eliminated. The study highlights the importance of using formal methods in project selection and target specification, leading to reduced planning time, increased success rate, and higher revenues for production systems.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Hamed Jafarzadeh et al.
Summary: This paper presents a comprehensive method for prioritizing projects by addressing the challenges of uncertainty, reliability, systematic identification of selection criteria, and robustness in decision making. The method integrates Z-numbers theory with Quality Function Development, four Multi-Criteria Decision-Making methods, ensemble ranking aggregation, and sensitivity analysis to achieve more effective project prioritization.
DECISION SUPPORT SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Clement Nartey et al.
Summary: The paper proposes two solutions for optimizing storage requirements on the blockchain - an improved hybrid architecture design and the AT-MOPSO algorithm. The AT-MOPSO algorithm shows better results in cloud storage cost and query probability optimization compared to other MOPSO algorithms, achieving 52% energy efficiency compared to NSGA-III. Additionally, the benefits of applying AT-MOPSO to existing blockchain systems are demonstrated using the BISS industrial blockchain architecture.
EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING
(2022)
Article
Computer Science, Artificial Intelligence
Amin Mahmoudi et al.
Summary: The study proposes a framework to help project-oriented organizations select the most appropriate portfolio based on organizational resilience strategy, by identifying portfolios, clustering projects using Elbow and Fuzzy C-Means methods, scoring projects with stakeholders' opinions and Robust Ordinal Priority Approach, and selecting the best portfolio linked to the organizational resilience strategy.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Automation & Control Systems
Mahmoud Awad et al.
Summary: This article presents the use of evolutionary algorithms, specifically NSGA-II and NSGA-III, to solve portfolio optimization problems with two and three objectives respectively. The Karush-Kuhn-Tucker Proximity Measure is used to evaluate the convergence of solutions and provide insights into Pareto optimal solutions.
INTELLIGENT AUTOMATION AND SOFT COMPUTING
(2022)
Review
Management
Miguel Saiz et al.
Summary: Project portfolio management and optimization are critical activities across various industries. This paper presents a clustering map of existing research in the field to identify main trends and approaches from different scientific communities, offering insights and emerging trends for researchers and practitioners.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Mojtaba Ranjbar et al.
Summary: This study utilizes a fuzzy hybrid multi-criteria method and a fuzzy bi-objective mathematical programming model to address the project portfolio selection and scheduling problem, optimizing the project portfolio through weighted qualitative criteria and a bi-objective fuzzy mathematical model.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Management
George Mavrotas et al.
Summary: The study proposes a method for selecting R&D project portfolios dealing with uncertainty in evaluation, using multicriteria analysis, mathematical programming, and Monte Carlo simulation. Through an iterative process, the final portfolio of R&D projects is gradually converged, addressing the uncertainty in expert evaluation.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Information Science & Library Science
Francisco Valverde-Alulema et al.
DATA BASE FOR ADVANCES IN INFORMATION SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Aghil Hamidi Hesarsorkh et al.
Summary: This study presents a mathematical programming model that simultaneously selects and schedules the optimal portfolio of R&D projects to address market and technical uncertainties in pharmaceutical companies. The model considers both technical and market risks, using a robust possibilistic programming approach to maximize the mean value of the R&D project portfolio. It serves as a strategic decision-making tool for pharmaceutical company managers to analyze investment scenarios and select a balanced portfolio.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Management
Juuso Liesio et al.
Summary: The study finds that the field of PDA is closely tied to practice, with many articles presenting real applications or containing illustrative examples motivated by practical applications. There is great potential in leveraging PDA concepts to derive recommendations for problems that may not have been traditionally viewed as PDA problems, as well as promoting the crossfertilization of conceptual and methodological advances across different application areas, and ensuring that new methodological advances are systematically evaluated through engagements with real decision makers.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Libiao Bai et al.
Summary: This research proposes a method based on complex network theory to select a robust project portfolio, consisting of three phases: decomposing strategic goals, determining the approach degrees between projects and sub-goals; determining the coupling coordination degree of the project portfolio; obtaining the optimal project portfolio that considers the robustness of the project portfolio network.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Alireza Sadeghi et al.
Summary: The study proposes a method combining EmcSVM and fuzzy NSGA-II to optimize trend classification and trading in the Forex market, outperforming existing systems with 80.8% precision, 72.4% recall, 94.1% annual ROI, and 0.58% draw down.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Mohammad A. Abido et al.
Summary: The study proposed a modified Multi-Objective Evolutionary Programming (MOEP) algorithm to solve scheduling problems of multi-mode activities, outperforming the benchmarked algorithms of SPEA-II and NSGA-II in terms of diversity and quality of the Pareto optimal set.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Soumen Atta et al.
Summary: The multi-objective MCLP with customers' preferences deals with maximizing the sum of customer demands and preferences covered by a fixed number of facilities. A Pareto-based multi-objective harmony search algorithm (MOHSA) is proposed to tackle this problem and outperforms the well-known NSGA-II in terms of computation time.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Ganivada Phanindra Kumar et al.
Summary: This article proposes an islanding detection scheme based on frequency and phase angle information obtained from mu PMU. The advantage of this scheme is that it does not require the establishment of thresholds and is independent of power mismatch conditions.
IEEE SYSTEMS JOURNAL
(2021)
Article
Biochemical Research Methods
Surama Biswas et al.
Summary: In this study, four algorithms based on the Archived Multi Objective Simulated Annealing (AMOSA) framework were proposed for parameter learning in Recurrent Neural Network (RNN) modeling of Gene Regulatory Network (GRN). Comparative studies on performance metrics, including recall, precision and f1 score, showed that the modified algorithms, AMOFSA and AMOTSA, outperformed AMOSAR and other state-of-the-art algorithms in terms of the number of GRNs obtained in the final non-dominated front.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2021)
Article
Computer Science, Information Systems
Gilberto Rivera et al.
Summary: This paper introduces a mathematical model based on compromise programming and fuzzy outranking to support Decision Makers in making real-time decision analysis for multi-criteria project portfolios. The model relaxes the problem of rapidly optimizing portfolios while preserving the beneficial properties of the DM's preferences expressed by outranking relations.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Information Systems
Ali Ahrari et al.
Summary: The study introduces a new information-sharing strategy and prediction model based on adjacent solutions to improve the robustness of multi-model prediction methods, demonstrating its effectiveness. Additionally, a similarity metric is introduced for multiobjective optimization, and a weighted pointwise prediction method (WPPM) based on this metric is developed.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Mohamed Abouhawwash et al.
Summary: The R-NSGA-II algorithm aims to find Pareto-optimal points close to aspiration points in the objective space, and it has been modified in this paper using the KKTPM and ASF metrics.
JOURNAL OF HEURISTICS
(2021)
Article
Computer Science, Information Systems
Jing Chen et al.
Summary: This study proposes a resource allocation algorithm for emergent demands in cloud computing, establishes a multi-objective optimization model, and presents an improved evolutionary algorithm, RAA-PI-NSGAII, which accelerates solving speed and improves the quality and distribution uniformity of the solution set.
JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS
(2021)
Article
Automation & Control Systems
Yuan Liu et al.
Summary: The Pareto-based approach is not well suited for optimization problems with a large number of objectives, prompting the proposal of a new algorithm in this article to address this issue. The algorithm tackles the problem by eliminating DRSs using an interquartile range method and balancing convergence and diversity through a penalty mechanism of alternating operations. Experimental results show that the proposed algorithm generally outperforms its competitors on a variety of test functions with 3-15 objectives.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Multidisciplinary Sciences
Omid Kebriyaii et al.
Summary: Time, cost, and quality are important factors in construction projects, and a multi-objective mathematical programming model has been developed in this study to address trade-off scheduling problems while considering the time value of money. Results show that considering the time value of money can prevent cost overrun in projects, and the MOGWO algorithm is found to outperform other algorithms in this context.
Article
Computer Science, Artificial Intelligence
Samaneh Zolfaghari et al.
Summary: Resource management is crucial for the success of project implementation, and optimizing project portfolio selection and flexible resource management can enhance profitability. Introducing a new solution approach based on triangular interval-valued fuzzy random variables provides a more accurate description of real-world project situations.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Automation & Control Systems
Liang-Hong Wu et al.
Summary: The study proposes a project selection method based on stochastic dominance and fuzzy theory, tested with real-world project data, resulting in significant improvements in risk assessment and project portfolio selection. The research provides managers with methods to estimate value and identify uncertainty factors in managing project portfolios.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2021)
Article
Mathematics
Mohammed Algarni et al.
Summary: The use of nano-enhanced phase change material (NePCM) in latent heat thermal energy storage (LHTES) systems significantly impacts melting/solidification duration and stored energy. This study utilized a hybrid approach involving design of experiments (DOE), computational fluid dynamics (CFD), artificial neural networks (ANNs), multi-objective optimization (MOO), and multi-criteria decision making (MCDM) to optimize nano-additives properties in a shell and tube LHTES system containing paraffin wax as a phase change material (PCM). Multiple optimization variables related to nano-additive properties were considered, with the primary goal of reducing melting duration and increasing total stored energy.
Article
Chemistry, Multidisciplinary
Eduardo Fernandez et al.
Summary: This paper introduces a new approach to group multi-objective optimization, which maximizes the overall group satisfaction by comparing satisfaction and dissatisfaction among group members. The proposed method is more general, capable of handling different objective values, imperfect resource information, and various other scenarios.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Information Systems
Carolina Lino Martins et al.
Summary: The authors proposed a multicriteria web-based decision support system for resource allocation in higher education organizations, which was empirically tested to show its effectiveness in providing clear vision and transparency of the resource allocation system.
INTERNATIONAL JOURNAL OF DECISION SUPPORT SYSTEM TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Rudolf Vetschera et al.
Summary: Portfolio decision models are important in decision analysis due to the complexity of constructing portfolios. This paper introduces a method to represent interactions between items in a portfolio and develops various bounds for performance estimation. Computational studies show that the proposed bounds frequently provide a good approximation of actual outcomes.
INTERNATIONAL JOURNAL OF DECISION SUPPORT SYSTEM TECHNOLOGY
(2021)
Review
Management
Charles Audet et al.
Summary: In recent years, there has been significant growth in the development of new algorithms for multiobjective optimization, with a large number of performance indicators introduced to measure the quality of Pareto front approximations. A total of 63 performance indicators are reviewed in this work, categorized into four groups based on their properties: cardinality, convergence, distribution, and spread. Applications of these indicators are also presented.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Fernando Luiz Rosa Mussoi et al.
Summary: The study introduces an integrated multicriteria decision-making methodology, including optimization and solutions ranking. The optimization module uses a multi-objective genetic algorithm to find Pareto-optimal portfolios, while the decision support module ranks project portfolios based on TOPSIS and SMART.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Vahid Mohagheghi et al.
Summary: Project portfolio selection considers goals derived from firm strategies and missions, with recent attention towards sustainability and resilience. The simultaneous consideration of resilience and sustainability in business environments is a new trend. A novel resilient-sustainable project portfolio evaluation and optimization process has been introduced to improve decision-making in firms’ project selection.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2021)
Proceedings Paper
Business
Carlos Roberto Pinheiro et al.
Summary: Enterprise Architecture (EA) is a coherent set of principles, methods, and models used to design an organizational structure and align it with strategic objectives. Enterprise Architecture Management (EAM) involves creating models representing different viewpoints for managing company concerns on IT landscape, aiming to automate modeling activities for faster and more agile architectural decision making. EA Mining uses data mining techniques to automate the creation or update of EA models, identifying aspects, techniques, and challenges of EA modeling automation.
2021 IEEE 23RD CONFERENCE ON BUSINESS INFORMATICS, CBI 2021, VOL 2
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Richard Romero Izurieta et al.
Summary: Public organizations in Ecuador have a low level of information security management capacity, with 70% at a Formative level and 22% at a Managed level. To manage information security optimally, it is necessary to start from strategic planning to achieve the organization's objectives.
2021 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI 2021)
(2021)
Article
Computer Science, Information Systems
Alhanof Almutairi et al.
Summary: ES adaptability is essential for organizations to manage uncertainties and continue providing services that meet customer expectations. However, many top managers may not fully understand the concept, leading to inaccurate assessment of the current state of their implemented ES.
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Mehdi Abedi et al.
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(2020)
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Computer Science, Artificial Intelligence
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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE
(2020)
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P. D. Zegzhda et al.
AUTOMATIC CONTROL AND COMPUTER SCIENCES
(2020)
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Environmental Sciences
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VTH INTERNATIONAL INNOVATIVE MINING SYMPOSIUM
(2020)
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INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2019)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Ferda Ozdemir Sonmez
10TH INT CONF ON EMERGING UBIQUITOUS SYST AND PERVAS NETWORKS (EUSPN-2019) / THE 9TH INT CONF ON CURRENT AND FUTURE TRENDS OF INFORMAT AND COMMUN TECHNOLOGIES IN HEALTHCARE (ICTH-2019) / AFFILIATED WORKOPS
(2019)
Proceedings Paper
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INTELLIGENT SYSTEMS IN CYBERNETICS AND AUTOMATION CONTROL THEORY
(2019)
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Hisao Ishibuchi et al.
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(2018)
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Pedro Sousa et al.
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(2018)
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Operations Research & Management Science
Sukono et al.
4TH INTERNATIONAL CONFERENCE ON OPERATIONAL RESEARCH (INTERIOR)
(2018)
Review
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INFORMATION SYSTEMS FRONTIERS
(2017)
Proceedings Paper
Computer Science, Information Systems
Diogo Proenca et al.
2017 IEEE 19TH CONFERENCE ON BUSINESS INFORMATICS (CBI), VOL 1
(2017)
Proceedings Paper
Robotics
E. D. Bravo Solis et al.
2015 12TH LATIN AMERICAN ROBOTICS SYMPOSIUM AND 2015 3RD BRAZILIAN SYMPOSIUM ON ROBOTICS (LARS-SBR)
(2015)
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Computer Science, Theory & Methods
Nery Riquelme et al.
2015 XLI LATIN AMERICAN COMPUTING CONFERENCE (CLEI)
(2015)
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IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
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