Article
Operations Research & Management Science
Musa Caglar, Sinan Gurel
Summary: This article examines the project portfolio selection problem faced by research councils in project and call-based R&D grant programs. By modeling project expenditure and using a mixture distribution and chance-constrained model, the study aims to increase budget utilization and achieve a higher number of successfully completed projects. These are important metrics for public decision-makers.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Hongbo Li, Rui Chen, Xianchao Zhang
Summary: In this study, we propose a stochastic programming model for the uncertain public R&D project portfolio selection problem and transform it into an equivalent deterministic second-order cone programming model. Through simulation and computational experiments, we analyze the impacts of various factors on the project portfolio performance.
Article
Business, Finance
Xianhe Wang, Yuliang Ouyang, You Li, Shu Liu, Long Teng, Bo Wang
Summary: This article proposes a portfolio selection model that integrates prospect theory and disappointment theory, considering emotional factors and providing a comprehensive depiction of individuals' decision-making processes in uncertain situations.
FINANCE RESEARCH LETTERS
(2023)
Article
Computer Science, Artificial Intelligence
Alejandro Santiago, Bernabe Dorronsoro, Hector J. Fraire, Patricia Ruiz
Summary: mu FAME is a new accurate Micro Genetic Algorithm proposed for multi-objective optimization problems, featuring high elitism and fast convergence achieved by directly applying evolution on the Pareto front approximation. It utilizes a Fuzzy Inference System to overcome diversity loss caused by high elitism and promote both diversity and accuracy of solutions. The algorithm is suitable for problems with computationally heavy fitness functions and exhibits great performance in comparison with state-of-the-art algorithms on various benchmark problems.
SWARM AND EVOLUTIONARY COMPUTATION
(2021)
Article
Computer Science, Interdisciplinary Applications
Ozge Sahin Zorluoglu, Ozgur Kabak
Summary: This study aims to design an interactive process to integrate project selection and scheduling processes in project management. For this purpose, a new multi-objective programming model is proposed, and projects are selected and scheduled based on belief degrees.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Information Systems
Sanjay Yadav, Arun Kumar, Mukesh Kumar Mehlawat, Pankaj Gupta, Vincent Charles
Summary: This paper proposes a sustainable financial portfolio selection approach using an intuitionistic fuzzy framework, consisting of three stages. The assets are ethically screened in the first stage, sustainability scores are calculated based on social, environmental, and economic criteria in the second stage, and a multi-objective financial portfolio selection model is developed in the third stage. Investors can choose efficient and sustainable financial portfolios based on their preferences.
INFORMATION SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Xiaomin Gong, Changrui Yu, Liangyu Min, Zhipeng Ge
Summary: This paper discusses fuzzy portfolio selection problems under bounded rationality, proposing a regret cross-efficiency (RCE) evaluation model and a multi-objective portfolio selection model based on regret theory, incorporating the uncertainty in data.
APPLIED SOFT COMPUTING
(2021)
Article
Business
Zsolt T. Kosztyan, Attila Katona, Kurt Kuppens, Maria Kisgyorgy-Pal, Andreas Nachbagauer, Tibor Csizmadia
Summary: Joint R&D&I projects can improve performance but also pose project-related risks. By creating a project portfolio, one can better plan budgets, timelines, and manage risks, resulting in improved relative costs and output.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Computer Science, Artificial Intelligence
Alejandro Estrada-Padilla, Claudia Gomez-Santillan, Hector Joaquin Fraire-Huacuja, Laura Cruz-Reyes, Nelson Rangel-Valdez, Maria Lucila Morales-Rodriguez, Hector Jose Puga-Soberanes
Summary: This paper proposes a new non-evolutionary GRASP/Δ algorithm for solving the multi-objective portfolio optimization problem with fuzzy trapezoidal parameters. The algorithm improves the efficiency of solution by using local search and an efficient local computation strategy, and its competitiveness is demonstrated through experiments compared to other state-of-the-art algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Review
Green & Sustainable Science & Technology
Dalton Garcia Borges de Souza, Erivelton Antonio dos Santos, Nei Yoshihiro Soma, Carlos Eduardo Sanches da Silva
Summary: Research and Development (R&D) Project Portfolio Selection (PPS) is a crucial strategic process for various companies, involving project selection methods, solving algorithms, and Multi-Criteria Decision Making (MCDM) methods. Despite advancements, there is still room for a systematic literature review to understand standard practices and research opportunities in the field.
Article
Business, Finance
Zhi Wang, Xuan Zhang, ZheKai Zhang, Dachen Sheng
Summary: This paper presents a general approach for optimizing a credit portfolio by minimizing the default risk of the entire portfolio. It introduces quadratic weighting and a novel bivariate intensity model to measure default risk, and utilizes a multi-objective genetic algorithm to improve optimization efficiency.
BORSA ISTANBUL REVIEW
(2022)
Article
Computer Science, Artificial Intelligence
Xiaoliang Ma, Jian Chen, Yiwen Sun, Zexuan Zhu
Summary: Portfolio selection aims to achieve an optimal trade-off between profit and risk by considering multiple optimization objectives. The use of expert acknowledge-based fuzzy number variables for modeling the return of risky assets improves the accuracy of return estimation. An assistant reference point guided evolutionary algorithm is proposed to solve this multi-objective portfolio problem efficiently and effectively.
SWARM AND EVOLUTIONARY COMPUTATION
(2021)
Article
Computer Science, Artificial Intelligence
Xiaoxia Huang, Kwon Ryong Hong, Jang Su Kim, Il Jong Choe
Summary: This paper discusses a multi-objective mean-variance model and its solution algorithms for project selection considering synergy under uncertain environment. The effect of uncertainty and synergy on project selection is analyzed and new solution algorithms are proposed. Numerical experiments show the performance of the proposed algorithms and a numerical example is given to demonstrate the validity of the model.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2022)
Article
Computer Science, Cybernetics
Mohammadali Zarjou, Mohammad Khalilzadeh
Summary: This study developed a model for project portfolio selection considering organizational goals such as budgets, cash flow, and reinvestment strategy. A multi-objective mathematical programming model was proposed, which took into account social, environmental, and financial aspects as project portfolio selection objectives. The study identified and ranked sustainability indicators using the fuzzy best-worst method.
Article
Environmental Sciences
Kaili Wu, Jingchun Feng, Sheng Li, Ke Zhang, Daisong Hu
Summary: This paper discusses the selection of the water environment restoration project portfolio (WERP). By analyzing the project's multidimensional property and operation mode, this paper develops the chance and management constraints of WERP from the perspectives of public service and enterprise operation. Furthermore, a multi-objective mixed integer linear programming model is proposed using the expectation method and fuzzy chance constraint programming method. The results show that our proposed method achieves a balance between economic and water environment restoration objectives and effectively manages the risk of exceeding the WERP capacity through market-based approaches. However, further examination of the impact of sub-projects and integration of evolutionary algorithms are needed to enhance the model's efficiency.
Article
Engineering, Multidisciplinary
P. Kumar, G. Panda, U. C. Gupta
SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES
(2018)
Article
Operations Research & Management Science
P. Kumar, A. K. Bhurjee
Summary: This paper investigates a multiple objective optimization problem with intervals as decision variables and parameters. The existence of a solution to this problem is studied by parameterizing the intervals. A methodology is proposed to find the t omega-efficient solution of the problem. The original problem is transformed into an equivalent deterministic problem, and the relationship between solutions of both is established. Finally, the methodology is validated through numerical examples.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
P. Kumar, A. K. Bhurjee
Summary: This article focuses on the nonlinear enhanced interval optimization problem and presents a methodology for determining efficient solutions. The theoretical justification for the existence of solutions is discussed, and numerical examples are provided to support the theoretical development.
Article
Operations Research & Management Science
P. Kumar, Jyotirmayee Behera, A. K. Bhurjee
Summary: This paper focuses on developing an interval mean-VaR portfolio optimization model with the objective of minimizing VaR. The methodology used combines interval analysis with parametric representation of the interval to obtain an efficient investment strategy. The theoretical developments are illustrated using historical data from the National Stock Exchange in India.
Proceedings Paper
Mathematics, Interdisciplinary Applications
Sheshma Kiran Kumari, P. Kumar, J. Priya, S. Surya, A. K. Bhurjee
11TH NATIONAL CONFERENCE ON MATHEMATICAL TECHNIQUES AND APPLICATIONS
(2019)
Article
Multidisciplinary Sciences
P. Kumar, G. Panda, U. C. Gupta
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2018)
Article
Operations Research & Management Science
P. Kumar, G. Panda
Proceedings Paper
Mathematics, Applied
Mrinal Jana, Pankaj Kumar, Geetanjali Panda
MATHEMATICS AND COMPUTING
(2015)
Article
Information Science & Library Science
A. K. Bhurjee, P. Kumar, G. Panda
JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES
(2015)
Article
Operations Research & Management Science
Pankaj Kumar, Geetanjali Panda, U. Gupta
Proceedings Paper
Computer Science, Artificial Intelligence
P. Kumar, G. Panda, U. C. Gupta
2013 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ - IEEE 2013)
(2013)
Article
Mathematics, Applied
Junfeng Cao, Ke Chen, Huan Han
Summary: This paper proposes a two-stage image segmentation model based on structure tensor and fractional-order regularization. In the first stage, fractional-order regularization is used to approximate the Hausdorff measure of the MS model. The solution is found using the ADI scheme. In the second stage, thresholding is used for target segmentation. The proposed model demonstrates superior performance compared to state-of-the-art methods.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2024)
Article
Mathematics, Applied
Dylan J. Oliver, Ian W. Turner, Elliot J. Carr
Summary: This paper discusses a projection-based framework for numerical computation of advection-diffusion-reaction (ADR) equations in heterogeneous media with multiple layers or complex geometric structures. By obtaining approximate solutions on a coarse grid and reconstructing solutions on a fine grid, the computational cost is significantly reduced while accurately approximating complex solutions.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2024)
Article
Mathematics, Applied
Nathan V. Roberts, Sean T. Miller, Stephen D. Bond, Eric C. Cyr
Summary: In this study, the time-marching discontinuous Petrov-Galerkin (DPG) method is applied to the Vlasov equation for the first time, using backward Euler for a Vlasov-Poisson discretization. Adaptive mesh refinement is demonstrated on two problems: the two-stream instability problem and a cold diode problem.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2024)
Article
Mathematics, Applied
Yizhi Sun, Zhilin Sun
Summary: This work investigates the convexity of a specific class of positive definite probability measures and demonstrates the preservation of convexity under multiplication and intertwining product. The study reveals that any integrable function on an interval with a polynomial expansion of fast absolute convergence can be decomposed into a pair of positive convex interval probabilities, simplifying the study of interval distributions and discontinuous probabilistic Galerkin schemes.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2024)
Article
Mathematics, Applied
Bhagwan Singh, Komal Jangid, Santwana Mukhopadhyay
Summary: This paper examines the prediction of bending characteristics of nanoscale materials using the Moore-Gibson-Thompson thermoelasticity theory in conjunction with the nonlocal strain gradient theory. The study finds that the stiffness of the materials can be affected by nonlocal and length-scale parameters, and the aspect ratios of the beam structure play a significant role in bending simulations.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2024)
Article
Mathematics, Applied
Guoliang Wang, Bo Zheng, Yueqiang Shang
Summary: This paper presents and analyzes a parallel finite element post-processing algorithm for the simulation of Stokes equations with a nonlinear damping term, which integrates the algorithmic advantages of the two-level approach, the partition of unity method, and the post-processing technique. The algorithm generates a global continuous approximate solution using the partition of unity method and improves the smoothness of the solution by adding an extra coarse grid correction step. It has good parallel performance and is validated through theoretical error estimates and numerical test examples.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2024)
Article
Mathematics, Applied
Hao Xu, Zeng-Qi Wang
Summary: Fluid flow control problems are crucial in industrial applications, and solving the optimal control of Navier-Stokes equations is challenging. By using Oseen's approximation and matrix splitting preconditioners, we can efficiently solve the linear systems and improve convergence.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2024)
Article
Mathematics, Applied
Zhengya Yang, Xuejuan Chen, Yanping Chen, Jing Wang
Summary: This paper focuses on the high-order stable numerical solutions of the time-space fractional diffusion equation. The Fourier spectral method is used for spatial discretization and the Spectral Deferred Correction (SDC) method is used for numerical solutions in time. As a result, a high-precision numerical discretization scheme for solving the fractional diffusion equation is obtained, and the convergence and stability of the scheme are proved. Several numerical examples are presented to demonstrate the effectiveness and feasibility of the proposed numerical scheme.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2024)