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Computer Science, Interdisciplinary Applications
Mohsen Mohammadi, Monica Gentili
Summary: This paper examines the outcome range problem in linear programming, proposing two approximation methods to solve it and demonstrating the relevance through a real case study.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
Tao Wang, Dayi Qu, Hui Song, Shouchen Dai
Summary: This paper proposes a hierarchical framework to address the decision making, planning, and control problem of autonomous vehicles in complex driving environments. High-level decision making is implemented by a finite-state machine, and a cluster of quintic polynomial equations is established to generate the path connecting the initial position to the candidate target positions. The speed profile is generated considering the motion state constraints and collision avoidance, and the planned path and speed profile are sent to the lower level control module for trajectory tracking control.
Article
Management
Beste Basciftci, Shabbir Ahmed, Siqian Shen
Summary: This paper discusses a distributionally robust facility location problem, highlighting the significant impact of facility location decisions on customer demand. The proposed decision-dependent distributionally robust optimization model demonstrates superior performance in profit and service quality across different scenarios.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Environmental Sciences
Qianqian Zhang, Zhong Li, Wendy Huang
Summary: The proposed ICCQP-WQM model effectively incorporates uncertainties and provides different cost-effective schemes for seasonal water quality management.
ENVIRONMENTAL RESEARCH
(2021)
Article
Mathematics, Applied
Fatemeh Salary Pour Sharif Abad, Mehdi Allahdadi, Hasan Mishmast Nehi
Summary: This paper introduces three algorithms to obtain the optimal solution set for interval linear fractional programming models. One algorithm obtains the OS set by solving two sub-models, while the other two algorithms only obtain a single feasible OS.
Article
Green & Sustainable Science & Technology
Yang Zhou, Bing Li, Jingcheng Han, Guojian He, Keyi Wang, Chunjiang An, Yuefei Huang
Summary: Increasing water-use efficiency is crucial for sustainable water management, especially in agriculture, which is the dominant sector for water use. This study proposes a multi-objective decision support model tool that considers risks and robustness to explore water-efficient agricultural development schemes and assess their environmental impacts. The tool integrates economic growth, water use objectives, and pollution control requirements to provide insights into the trade-offs between resource efficiency and environmental impact. A case study in a Chinese city demonstrates how the tool can reduce water usage in agriculture while improving economic productivity. The results suggest that stricter phosphorus control requirements can lead to better pollution control in the agricultural system. Overall, this tool showcases the applicability of using a systems analysis approach to guide the transition towards water-efficient and low-impact agricultural practices.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Engineering, Multidisciplinary
Mridul Patel, Jyotirmayee Behera, Pankaj Kumar
Summary: The presented article focuses on a multi-objective interval fractional optimization problem based on a linear function. The design variables are assumed to be closed intervals using the parametric form of an interval. The original problem is transformed into an equivalent multi-objective interval linear programming problem with closed interval design variables. By utilizing the weighted-sum method, the problem is further converted into a classical single-objective problem without interval uncertainty. The model's solutions are theoretically justified by proving their existence. Finally, a numerical example and a case study on agricultural planting structure optimization problem with hypothetical data are provided to support the recommended technique for the model.
ENGINEERING OPTIMIZATION
(2023)
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Automation & Control Systems
Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu
Summary: This paper proposes an individualized interval-valued decision rule (I2DR) in the continuous treatment setting. The jump interval-learning method is used to derive an optimal I2DR, which maximizes the expected outcome. Compared to traditional decision rules, I2DR provides an interval of treatment options for each individual, offering greater flexibility in practice.
JOURNAL OF MACHINE LEARNING RESEARCH
(2023)
Article
Engineering, Manufacturing
Rongchuan He, Ye Lu
Summary: The study addresses the price-setting newsvendor problem where retailers may have limited information on demand models, which creates a gap between academic research and practical applications. A robust optimization approach is proposed to minimize maximum regret, and extensive numerical studies demonstrate its superior performance compared to the regression method.
PRODUCTION AND OPERATIONS MANAGEMENT
(2021)
Article
Computer Science, Information Systems
Maha M. Saeed Mohammad, Saleem Abdullah, M. M. Al-Shomrani
Summary: This paper focuses on developing similarity and distance measures for linear Diophantine fuzzy numbers and proposes a new emergency decision making method based on these measures. The proposed method is applied to medical diagnosis for COVID-19 virus.
Article
Computer Science, Software Engineering
Meilun Li, Andrea Turrini, Ernst Moritz Hahn, Zhikun She, Lijun Zhang
Summary: This paper introduces the probabilistic preference-based planning problem and its solution methods, addressing the task achievement and performance optimization issues in Markov decision processes.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Yuan Zou
Summary: Bayesian decision models, using probability theory, are widely used in practical applications for estimation, prediction, and decision support. However, these models have two main deficiencies: subjective judgment in quantization of prior probabilities and the inability to handle non-stochastically stable information using point-valued probabilities. Soft set theory, as an emerging mathematical tool, introduces the concept of soft probability, which can handle various types of stochastic phenomena, including non-stochastically stable ones.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2023)
Article
Green & Sustainable Science & Technology
Mostafa Ekhtiari, Mostafa Zandieh, Erfan Babaee Tirkolaee
Summary: This study focuses on the problem of dam site selection and proposes a new model based on NCP and stochastic programming for handling uncertainty. By using the IGDEMATEL method to determine criterion weights and evaluating the results through simulation, similar outcomes to the simulation model were obtained. This research contributes to addressing the issue of dam site selection in water resources management.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Green & Sustainable Science & Technology
Xi Yang, Zhihe Chen
Summary: Reasonable water resources management is crucial for sustainable development. This study proposes a decision-making framework combining interval TOPSIS and a multi-sensitivity strategy for robust water resources management under uncertainty.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Artificial Intelligence
Sapan Kumar Das
Summary: This article addresses a fully fuzzy triangular linear fractional programming problem with parameters and decision variables characterized by triangular fuzzy numbers. A new concept is proposed to reduce computational complexity without sacrificing effectiveness. Mathematical models are used to evaluate the legitimacy, usefulness, and applicability of the method, showing that the novel strategies are superior to current techniques.
COMPLEX & INTELLIGENT SYSTEMS
(2022)
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Computer Science, Theory & Methods
Yonggang Li, Peijun Guo
FUZZY SETS AND SYSTEMS
(2015)
Article
Computer Science, Theory & Methods
Chao Wang, Jing Li, Peijun Guo
FUZZY SETS AND SYSTEMS
(2015)
Article
Management
Chao Wang, Peijun Guo
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2017)
Article
Operations Research & Management Science
Xide Zhu, Peijun Guo
MATHEMATICAL METHODS OF OPERATIONS RESEARCH
(2017)
Editorial Material
Chemistry, Inorganic & Nuclear
Uwe Watjen, Pierino De Felice, Franz Josef Maringer
APPLIED RADIATION AND ISOTOPES
(2014)
Article
Management
Peijun Guo, Xiuyan Ma
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2014)
Article
Management
Peijun Guo, Yonggang Li
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2014)
Editorial Material
Chemistry, Inorganic & Nuclear
Antonio Bianchi, Enrique Garcia-Espana
INORGANICA CHIMICA ACTA
(2014)
Editorial Material
Infectious Diseases
Alan P. Johnson, Mitchell J. Schwaber, Evelina Tacconelli
JOURNAL OF ANTIMICROBIAL CHEMOTHERAPY
(2014)
Editorial Material
Mathematics, Applied
M. Van Daele, S. Vandewalle
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2014)
Editorial Material
Chemistry, Inorganic & Nuclear
Goran N. Kaluderovic, Ljiljana Jovanovic
Editorial Material
Engineering, Mechanical
Felice Arena, Giuseppe Muscolino, Antonina Pirrotta
PROBABILISTIC ENGINEERING MECHANICS
(2014)
Editorial Material
Chemistry, Applied
Felix Studt, Frank Abild-Pedersen, Thomas Bligaard, Anders Nilsson
TOPICS IN CATALYSIS
(2014)
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Management
Peijun Guo
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2019)
Article
Operations Research & Management Science
Xide Zhu, Peijun Guo
4OR-A QUARTERLY JOURNAL OF OPERATIONS RESEARCH
(2020)
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)