Article
Operations Research & Management Science
Liguo Jiao, Jae Hyoung Lee
Summary: This article considers a mathematical programming problem with uncertain data and multiple objective functions, proposing a robust counterpart using the worst-case approach. By employing the epsilon-constraint method, the problem is substituted by a class of scalar problems, leading to a zero duality gap result and discussion of solution relationships. The results demonstrate the tractability of finding robust efficient solutions to the original problem.
ANNALS OF OPERATIONS RESEARCH
(2021)
Article
Operations Research & Management Science
Yasmine Cherfaoui, Mustapha Moulai
Summary: This paper introduces a method for generating the set of efficient solutions for multiobjective integer linear plus linear fractional programming problems, which involves Branch-and-Bound exploration and cutting plane technique to eliminate inefficient solutions. The cutting plane technique reduces exploration's domain by considering the inefficiency of a solution in another problem.
ANNALS OF OPERATIONS RESEARCH
(2021)
Article
Engineering, Industrial
Javier Leon, Begona Vitoriano, John Hearne
Summary: Hazard reduction is a complex task that involves efforts to prevent and mitigate disaster consequences. Prescribed burning is a fuel management strategy to reduce wildfire hazard, but it impacts animal habitat and has uncertainties in scheduling. A mathematical programming model is proposed to schedule prescribed burns, considering uncertainty and safety criteria. The model aims to minimize worst-case achievement of criteria in different scenarios and is applied to a real case study in Andalusia, showing better performance than the risk-neutral solution.
Article
Operations Research & Management Science
Alireza Kabgani, Majid Soleimani-damaneh
Summary: We correct Theorem 4.1 in [Kabgani A, Soleimani-damaneh M. "Characterization of (weakly/properly/robust) efficient solutions in nonsmooth semi-infinite multiobjective optimization using convexificators. Optimization, 2018; 67: 217-235] and demonstrate that the error does not affect other results in the paper. Additionally, we present several new corollaries for this theorem.
Article
Management
Antonio Diglio, Juanjo Peiro, Carmela Piccolo, Francisco Saldanha-da-Gama
Summary: This paper investigates a districting problem with stochastic demands, aiming to find a balanced division with given probability. A two-phase heuristic method is developed, along with a simulation procedure to estimate the probability of balanced districting. Different probability distributions for demands are also explored.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Operations Research & Management Science
Yacine Chaiblaine, Mustapha Moulai
Summary: In this paper, an exact method is proposed to optimize a quadratic function over the efficient set of a multiobjective integer linear fractional program. The method solves a sequence of quadratic integer problems and reduces the search domain successively to eliminate dominated solutions, enhancing the method performance.
OPTIMIZATION LETTERS
(2022)
Article
Operations Research & Management Science
Fatima Bellahcene, Philippe Marthon
Summary: The proposed approach is applicable to multiobjective stochastic linear programming problems with continuous random variables. The minimum-risk criterion and the Chebyshev problem are utilized to find the optimal or epsilon optimal solution through an algorithm combining the bisection method and goal achievement probabilities. An illustrative example is provided to clarify the developed theory.
OPERATIONAL RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Teng Long, Qing-Shan Jia, Gongming Wang, Yu Yang
Summary: This paper presents an efficient and scalable real-time scheduling method for handling the charging demands of plug-in electric vehicles (PEV), demonstrating through simulations that the proposed method provides high computation efficiency and scalability while reducing operating costs for charging stations. Compared to existing methods, it outperforms in terms of charging policy search capabilities and performance guarantee.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Operations Research & Management Science
T. D. Chuong, V. H. Mak-Hau, J. Yearwood, R. Dazeley, M-T Nguyen, T. Cao
Summary: This paper investigates a convex quadratic multiobjective optimization problem with data uncertainty, finding robust (weak) Pareto solutions using linear matrix inequalities. It also demonstrates that the obtained optimality conditions can be verified via a robust Karush-Kuhn-Tucker condition. Additionally, a relaxation problem of a robust weighted-sum optimization program can be solved as a semidefinite programming (SDP) problem.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Agronomy
Peixi Tang, Nan Li, Mo Li, Fan Zhang, Qiang Fu, Yaowen Xu, Dong Liu
Summary: This study proposes an AquaCrop-based optimization modeling approach to improve the water use efficiency of rice farming. A multiobjective model is constructed to generate dynamic water production functions (WPFs) for rice under different hydrological years. Based on the obtained WPFs, a fuzzy credibility-constrained stochastic multiobjective programming (FCCSMOP) model is developed for irrigation water allocation. The proposed approach is applied to the Changgang irrigation district in northeast China and shows promising results in improving system efficiency and increasing planting income.
EUROPEAN JOURNAL OF AGRONOMY
(2023)
Article
Agronomy
Fan Zhang, Ningbo Cui, Shanshan Guo, Qiong Yue, Shouzheng Jiang, Bin Zhu, Xiuyun Yu
Summary: This study proposed a Copula-based stochastic multiobjective programming model for optimizing irrigation strategies to mitigate the negative impacts of seasonal agricultural droughts (SAD). The model uses regional net irrigation water demand and stream runoff to better characterize SAD. A case study in Meishan City of southwest China showed that the optimal irrigation strategies improved crop yields and the C-SMP demonstrated clear advantages in dealing with multiple conflicting objectives and the randomness of SAD scenarios.
AGRICULTURAL WATER MANAGEMENT
(2023)
Article
Computer Science, Artificial Intelligence
Hong Liu, Xudong Chen
Summary: This article introduces a chance-constrained multiobjective programming model to optimize order quantities in e-commerce inventory systems, considering the impact of promotional activities on demand fluctuations. By characterizing stochastic demand and prices with a normal distribution based on historical data, a novel method called rough approximation is designed to handle uncertainty efficiently. The proposed model, combined with a proxy ideal point-based genetic algorithm, offers decision makers a flexible solution to determine optimal order quantities for different promotional activity scales.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Mathematics
Chia-Nan Wang, Nhat-Luong Nhieu, Trang Thi Thu Tran
Summary: The study develops a stochastic multi-objective mixed-integer optimization model to ensure production efficiency in uncertainty conditions and satisfy sustainable development requirements. The model ensures the efficiency of the production system through optimization of objective functions related to economy, environment, and sociality.
Article
Operations Research & Management Science
Andrew Butler, Roy H. Kwon
Summary: This paper presents an alternative network layer architecture based on ADMM for solving medium-sized quadratic programs, which demonstrates computational advantages and efficiency compared to state-of-the-art layers.
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
(2023)
Article
Engineering, Multidisciplinary
Yasmine Cherfaoui, Mustapha Moula
Summary: This article proposes an exact method to optimize two preference functions over the efficient set of a multiobjective integer linear program (MOILP), and develops a branch-and-cut algorithm based on linear programming to find efficient solutions without explicitly enumerating all solutions. The branch and bound process, strengthened by efficient cuts and tests, allows pruning of a large number of nodes in the tree to avoid many solutions. An illustrative example and experimental study are provided.
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
(2021)
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)