Review
Operations Research & Management Science
M. Kandakoglu, G. Walther, S. Ben Amor
Summary: In this paper, the use of Multi-criteria Decision Analysis (MCDA) methods in project portfolio selection (PPS) problems is reviewed. The authors summarize the different modeling approaches involving MCDA methods, discuss the combination of MCDA with mathematical programming techniques, and analyze the drawbacks and recent advances in their combined utilization. The paper concludes by providing a decision tree visualization of the reviewed papers to guide researchers and practitioners in using MCDA methods in PPS.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Yi Chen, Aimin Zhou
Summary: This study proposes a new algorithm, F-MOEA/D, for portfolio optimization problem, which combines exact methods and decomposition approaches to achieve better optimization results within a limited time.
COMPLEX & INTELLIGENT SYSTEMS
(2022)
Review
Mathematics
Asmaa M. Hagag, Laila S. Yousef, Tamer F. Abdelmaguid
Summary: With the increasing number of alternative machines and continuous technological advancements, the machine selection problem has garnered interest from many researchers. This article provides a review of recent developments in using multi-criteria decision-making (MCDM) methods for machine selection in the manufacturing and construction industries. The selected articles are categorized based on the application area and the MCDM method employed. By focusing on the past five years, this paper identifies noteworthy trends in the development and utilization of these methods. The findings indicate a significant growth in the application of MCDM techniques for machine selection in both sectors, along with the successful development and implementation of decision-support tools and methods. Future research needs and directions are also discussed.
Article
Business
Qun Wu, Xinwang Liu, Jindong Qin, Ligang Zhou, Abbas Mardani, Muhammet Deveci
Summary: This paper aims to develop a hybrid SRI portfolio selection model using multi-criteria decision making and multi-objective optimization techniques. A case study on medical stock investment is conducted to demonstrate the robustness, effectiveness, and superiority of the proposed methodology.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Operations Research & Management Science
Maciej Nowak, Tadeusz Trzaskalik
Summary: The paper introduces a new interactive procedure based on trade-off analysis for solving stochastic discrete multiobjective programming problems with a finite number of stages, using project portfolio selection as an example. Despite the problem not being very large in size, its difficulty lies in the fact that projects are not implemented simultaneously.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Mathematics, Applied
Serkan Akbas, Turkan Erbay Dalkilic
Summary: With the development of technology, investors are increasingly relying on computer software to guide their investments. This study proposes a two-stage portfolio selection model that considers investment data and expert opinions to address the issue of investors achieving the same expected return and risk level. By developing mathematical models suitable for trapezoidal fuzzy numbers, a new hybrid portfolio selection algorithm is introduced. The algorithm is tested using stock data from the Dow Jones Index, comparing total return amounts obtained by different methods for investment in January 2021.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2021)
Review
Computer Science, Artificial Intelligence
Long Chen, Wei Pan
Summary: With the complex and uncertain nature of construction management, fuzzy multi-criteria decision making (FMCDM) has become popular for addressing diverse decision-makers' interests and conflicting objectives. This study comprehensively reviews FMCDM literature in construction management from 2007 to 2017 using a network approach, exploring the relationships between fuzzy sets (FSs), MCDM, and associated applications. The analysis of 165 published journal articles reveals the characteristics, strengths, and limitations of 37 single-hybrid and 17 multiple-hybrid FMCDM methods.
APPLIED SOFT COMPUTING
(2021)
Article
Operations Research & Management Science
Jia Liu, Zhiping Chen, Giorgio Consigli
Summary: The introduction of interval-based stochastic dominance (ISD) offers a new stochastic dominance relationship that spans preferences between different orders. Distinguishing between first-order and second-order stochastic dominance, ISD provides insights into decision theory and optimal financial allocation. The implications of ISD in the presence of discrete random variables are discussed and applied to a portfolio selection problem.
ANNALS OF OPERATIONS RESEARCH
(2021)
Article
Engineering, Marine
H. Diaz, C. Guedes Soares
Summary: This paper investigates the selection of an optimal port for offshore wind components storage and assembly to reduce transportation cost. The integrated multi-criteria decision method based on the Ranking Method and the Weighted Product Method is proposed. Twenty-one criteria are identified through data analysis and expert evaluation. Experts in the field evaluate the port selection criteria and establish a ranking to determine the best solution. The findings of this study could benefit port managers and marine transportation associations in improving port facilities and regulations.
Article
Environmental Sciences
Qiushuang Wei, Chao Zhou
Summary: This paper provides insights into electric vehicle supplier selection from the perspective of government agencies and public bodies using an integrated multi-criteria decision-making framework. Through a case study and analysis, it determines the importance of criteria such as bad environmental record, cost, quality, service, and environmental initiatives in electric vehicle supplier selection.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
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, Interdisciplinary Applications
Ioannis Gkioulekas, Lazaros G. Papageorgiou
Summary: This work presents a tree regression algorithm that optimally splits nodes into subsets using an optimization model and assesses partition quality with a statistical test. It also explores splitting nodes using multivariate decision rules to improve performance and computational efficiency. Introducing a novel mathematical model that selects an optimal set of variables for splitting on each node enhances the computational performance of the algorithm.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Mathematics, Applied
Qazi Shoeb Ahmad, Mohammad Faisal Khan, Naeem Ahmad
Summary: The best-worst method (BWM) and the multi-choice best-worst method (MCBWM) are effective approaches for addressing decision-making problems. This study proposes two mathematical programming models that consider multiple decision-makers and the uncertainty of choices. The models are novel in their mathematical structure and group decision-making approach.
Review
Engineering, Civil
Xingyu Zhu, Xianhai Meng, Min Zhang
Summary: Decision making is crucial for success in various sectors including construction, where Multiple Criteria Decision Making (MCDM) plays a significant role in solving complex problems. This study systematically reviewed 530 construction articles published from 2000 to 2019, categorizing them into seven major application areas and conducting bibliometric analysis to describe research trends. Potential challenges and future directions for the development of MCDM methods in construction were identified through qualitative discussion.
JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT
(2021)
Article
Automation & Control Systems
Maisa Kely de Melo, Rodrigo T. N. Cardoso, Tales A. Jesus
Summary: This paper proposes a multiobjective model predictive control (MO-MPC) for portfolio selection. The objective functions are defined using a multiperiod format and consider the expected wealth, variance, and conditional value at risk. The method also takes into account transaction costs, self-financing, and investment limits. By using a multiobjective genetic algorithm, a Pareto front is obtained and a Pareto optimal point is selected as the control action based on investor preferences. Numerical experiments using data from the Brazilian stock exchange show that the MO-MPC performs well in extreme financial market situations, effectively managing risk and return trade-offs.
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
(2022)
Article
Operations Research & Management Science
Panos Xidonas, Haris Doukas, George Mavrotas, Olena Pechak
ANNALS OF OPERATIONS RESEARCH
(2016)
Article
Economics
P. Xidonas, C. Hassapis, G. Bouzianis, C. Staikouras
COMPUTATIONAL ECONOMICS
(2018)
Article
Management
Panos Xidonas, George Mavrotas, Christis Hassapis, Constantin Zopounidis
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2017)
Article
Management
Vangelis Marinakis, Haris Doukas, Panos Xidonas, Constantin Zopounidis
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2017)
Article
Operations Research & Management Science
Panagiotis Xidonas, George Mavrotas, John Psarras
JOURNAL OF GLOBAL OPTIMIZATION
(2010)
Article
Management
P. Xidonas, G. Mavrotas, J. Psarras
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2010)
Article
Operations Research & Management Science
Panagiotis Xidonas, George Mavrotas, John Psarras
Article
Business, Finance
Panos Xidonas, George Mavrotas
QUANTITATIVE FINANCE
(2014)
Article
Economics
Panayotis G. Michaelides, Efthymios G. Tsionas, Konstantinos N. Konstantakis, Panos Xidonas
Article
Economics
Panos Xidonas, Christis Hassapis, John Soulis, Aristeidis Samitas
ECONOMIC MODELLING
(2017)
Article
Energy & Fuels
Haris Doukas, Panos Xidonas, Dimitris Angelopoulos, Dimitris Askounis, John Psarras
ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS
(2016)
Article
Environmental Studies
Vangelis Marinakis, Panos Xidonas, Haris Doukas
INTERNATIONAL JOURNAL OF GLOBAL ENERGY ISSUES
(2016)
Article
Management
Michael Doumpos, Panagiotis Xidonas, Sotirios Xidonas, Yannis Siskos
JOURNAL OF MULTI-CRITERIA DECISION ANALYSIS
(2016)
Article
Business, Finance
Panos Xidonas, George Mavrotas
EUROPEAN JOURNAL OF FINANCE
(2014)
Review
Management
Vinicius N. Motta, Miguel F. Anjos, Michel Gendreau
Summary: This survey presents a review of optimization approaches for the integration of demand response in power systems planning and highlights important future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Philipp Schulze, Armin Scholl, Rico Walter
Summary: This paper proposes an improved branch-and-bound algorithm, R-SALSA, for solving the simple assembly line balancing problem, which performs well in balancing workloads and providing initial solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Roshan Mahes, Michel Mandjes, Marko Boon, Peter Taylor
Summary: This paper discusses appointment scheduling and presents a phase-type-based approach to handle variations in service times. Numerical experiments with dynamic scheduling demonstrate the benefits of rescheduling.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Oleg S. Pianykh, Sebastian Perez, Chengzhao Richard Zhang
Summary: Efficient scheduling is crucial for optimizing resource allocation and system performance. This study focuses on critical utilization and efficient scheduling in discrete scheduling systems, and compares the results with classical queueing theory.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Review
Management
Hamed Jahani, Babak Abbasi, Jiuh-Biing Sheu, Walid Klibi
Summary: Supply chain network design is a large and growing area of research. This study comprehensively surveys and analyzes articles published from 2008 to 2021 to detect and report financial perspectives in SCND models. The study also identifies research gaps and offers future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Patrick Healy, Nicolas Jozefowiez, Pierre Laroche, Franc Marchetti, Sebastien Martin, Zsuzsanna Roka
Summary: The Connected Max-k-Cut Problem is an extension of the well-known Max-Cut Problem, where the objective is to partition a graph into k connected subgraphs by maximizing the cost of inter-partition edges. The researchers propose a new integer linear program and a branch-and-cut algorithm for this problem, and also use graph isomorphism to structure the instances and facilitate their resolution. Extensive computational experiments show that, if k > 2, their approach outperforms existing algorithms in terms of quality.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Victor J. Espana, Juan Aparicio, Xavier Barber, Miriam Esteve
Summary: This paper introduces a new methodology based on the machine learning technique MARS for estimating production functions that satisfy classical production theory axioms. The new approach overcomes the overfitting problem of DEA through generalized cross-validation and demonstrates better performance in reducing mean squared error and bias compared to DEA and C2NLS methods.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Stefano Nasini, Rabia Nessah
Summary: In this paper, the authors investigate the impact of time flexibility in job scheduling, showing that it can significantly affect operators' ability to solve the problem efficiently. They propose a new methodology based on convex quadratic programming approaches that allows for optimal solutions in large-scale instances.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Zhiqiang Liao, Sheng Dai, Timo Kuosmanen
Summary: Nonparametric regression subject to convexity or concavity constraints is gaining popularity in various fields. The conventional convex regression method often suffers from overfitting and outliers. This paper proposes the convex support vector regression method to address these issues and demonstrates its advantages in prediction accuracy and robustness through numerical experiments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Kuo-Hao Chang, Ying-Zheng Wu, Wen-Ray Su, Lee-Yaw Lin
Summary: The damage and destruction caused by earthquakes necessitates the evacuation of affected populations. Simulation models, such as the Stochastic Pedestrian Cell Transmission Model (SPCTM), can be utilized to enhance disaster and evacuation management. The analysis of SPCTM provides insights for government officials to formulate effective evacuation strategies.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Qinghua Wu, Mu He, Jin-Kao Hao, Yongliang Lu
Summary: This paper studies a variant of the orienteering problem known as the clustered orienteering problem. In this problem, customers are grouped into clusters and a profit is associated with each cluster, collected only when all customers in the cluster are served. The proposed evolutionary algorithm, incorporating a backbone-based crossover operator and a destroy-and-repair mutation operator, outperforms existing algorithms on benchmark instances and sets new records on some instances. It also demonstrates scalability on large instances and has shown superiority over three state-of-the-art COP algorithms. The algorithm is also successfully applied to a dynamic version of the COP considering stochastic travel time.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Bjorn Bokelmann, Stefan Lessmann
Summary: Estimating treatment effects is an important task for data analysts, and uplift models provide support for efficient allocation of treatments. However, evaluating uplift models is challenging due to variance issues. This paper theoretically analyzes the variance of uplift evaluation metrics, proposes variance reduction methods based on statistical adjustment, and demonstrates their benefits on simulated and real-world data.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Congzheng Liu, Wenqi Zhu
Summary: This paper proposes a feature-based non-parametric approach to minimizing the conditional value-at-risk in the newsvendor problem. The method is able to handle both linear and nonlinear profits without prior knowledge of the demand distribution. Results from numerical and real-life experiments demonstrate the robustness and effectiveness of the approach.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Laszlo Csato
Summary: This paper compares the performance of the eigenvalue method and the row geometric mean as two weighting procedures. Through numerical experiments, it is found that the priorities derived from the two eigenvectors in the eigenvalue method do not always agree, while the row geometric mean serves as a compromise between them.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Guowei Dou, Tsan-Ming Choi
Summary: This study investigates the impact of channel relationships between manufacturers on government policies and explores the effectiveness of positive incentives versus taxes in increasing social welfare. The findings suggest that competition may be more effective in improving sustainability and social welfare. Additionally, government incentives for green technology may not necessarily enhance sustainability.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)