Article
Management
Alan Kinene, Sebastian Birolini, Mattia Cattaneo, Tobias Andersson Granberg
Summary: This paper proposes an optimization model for the strategic design of charging networks for electric aircraft, aiming to prepare for and take full advantage of aviation electrification. The model optimizes the number of charging bases, connectivity, and population coverage for regional routes serving remote regions. The study demonstrates the practical insights and benefits of utilizing under-utilized regional airports and increasing the maximum aircraft range on a single charge.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Transportation
Mohsen Sadeghi, Iman Aghayan, Mehrdad Ghaznavi
Summary: The study proposed an optimization approach based on cuckoo search algorithm to solve the Transit Network Design and Frequency Setting Problem, considering multiple costs and aiming for sustainable design objectives. The results showed that the CS-based approach performed significantly in finding the optimal routes for the public transportation network.
TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH
(2021)
Article
Mathematics, Interdisciplinary Applications
Hongzhi Lin
Summary: The importance of traffic safety in transportation planning is underestimated, and it needs to be considered more thoroughly during the design of transportation networks. By proposing a bilevel programming model system, it is possible to effectively reduce the number of traffic accidents. Experimental studies show that these methods are valuable in designing a safer transportation network, although some sacrifice in total travel time may occur.
Review
Management
Teodor Gabriel Crainic, Bernard Gendron, Mohammad Rahim Akhavan Kazemzadeh
Summary: Multilayer network design is an important problem class that involves interwoven design decisions across different layers, with applications in transportation and telecommunications. This article presents a classification and survey of multilayer network design problems, along with a general modeling framework.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Yogita Singh Kardam, Kamal Srivastava, Pallavi Jain, Rafael Marti
Summary: This paper proposes a heuristic algorithm based on scatter search methodology for the Minimum Leaf Spanning Tree Problem (MLSTP), which is capable of generating spanning trees with a lower number of leaves compared to previous methods.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Cesar Rego, Frank Mathew
Summary: We develop a scatter search algorithm to solve the classical capacitated minimum spanning tree problem, including both homogeneous and heterogeneous variants. This problem is central in network design applications in industrial engineering, routing and logistics, and communication networks. Since it is an NP-Complete problem, heuristic solution methods are necessary to find high-quality solutions within practical time limits. Our proposed algorithm competes with the best algorithms in the literature and avoids complicated artifacts.
ADVANCES IN ENGINEERING SOFTWARE
(2023)
Article
Economics
Mike Hewitt, Fabien Lehuede
Summary: We propose a new approach to solving the Scheduled Service Network Design Problem (SSNDP), which involves modeling shipments routed on the physical network with enumerated consolidations. Compared to the traditional time-expanded network approach, the proposed formulation has a stronger linear relaxation and is less symmetric. Multiple speed-up techniques are presented to show that the consolidation-based formulation is easier to solve than the classical formulation based on a time-expanded network. A hybrid formulation that combines ideas from the consolidation and time-expanded network-based approaches is also proposed to address instances with large numbers of consolidations. It is shown that the hybrid formulation is easier to solve than both the pure consolidation-based formulation and the time-expanded network formulation.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2023)
Article
Green & Sustainable Science & Technology
Yuan Liu, Heshan Zhang, Tao Xu, Yaping Chen
Summary: This study proposes a simultaneous optimization model that considers flow assignment and vehicle capacity for transit network design, aiming to reduce total travel time and the number of transfers. It develops a heuristic algorithm to generate initial routes and allocate vehicles to each route based on flow share. The concept of vehicle difference is introduced to evaluate the distinction between actual allocated vehicles and required vehicles for each route. The optimization process based on vehicle difference ensures that the solution meets the constraints.
Article
Computer Science, Information Systems
Jingru Ren, Wenming Zhu
Summary: This paper proposes a two-stage local search strategy, called dual scatter search strategy, for generating automated test cases for path coverage. Experimental studies on twelve benchmark programs demonstrate that this strategy achieves the highest path coverage with the fewest test cases and running time.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2023)
Article
Transportation Science & Technology
Antoine Petit, Mehmet Yildirimoglu, Nikolas Geroliminis, Yanfeng Ouyang
Summary: This paper proposes an integrated methodological framework for designing a spatially heterogeneous bus route network and time-dependent service intervals to meet travel demand. Numerical experiments are used to demonstrate the applicability of the proposed model and conduct a detailed analysis on the impact of demand patterns on public transit network design, roadway congestion, and system performance.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Engineering, Industrial
Amir Hossein Barahimi, Alireza Eydi, Abdolah Aghaie
Summary: The research addresses the issue of increasing the link capacity in a dual-mode public transport network within urban infrastructure. By developing a mathematical model and using the PSO algorithm to solve the multi-objective bi-level model, the study was applied to a part of the urban transportation network in Tehran, Iran.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Engineering, Environmental
Jinkun Men, Guohua Chen, Lixing Zhou, Peizhu Chen
Summary: This study addresses the issue of considering multiple simultaneous HazMat shipments and proposes a multi-objective transportation network design model. The proposed algorithm is competitive in solving large-scale instances and effectively coordinates multiple HazMat transportation processes.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2022)
Review
Management
Claudia Archetti, Lorenzo Peirano, M. Grazia Speranza
Summary: This article provides an overview of the state of the art in multimodal freight transportation optimization, including different combinations of modes and emerging trends for future research.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Jan Philipp Mueller, Ralf Elbert, Simon Emde
Summary: Service network design is a crucial planning task for intermodal operators, and the inability to accurately predict transportation demand can lead to a stochastic design problem. Introducing ad-hoc modifications to planned schedules can result in substantial cost reductions, demonstrating superior performance compared to traditional approaches. Further analysis reveals a different solution structure and cost savings when schedule modifications are considered.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Siming Fu, Huanpeng Chu, Lu Yu, Bo Peng, Zheyang Li, Wenming Tan, Haoji Hu
Summary: This paper proposes a baseline-auxiliary expanding network design method to compensate for the binarization residual of features. By searching for auxiliary branches (AuxBranch), the intermediate feature maps are enhanced to mimic the feature output of a full-precision network. Additionally, a hybrid performance estimator (PE) is designed to efficiently search for binarization baseline and adjust computational complexity automatically.
PATTERN RECOGNITION
(2023)
Article
Energy & Fuels
Luca D'Acierno, Marilisa Botte
Article
Green & Sustainable Science & Technology
Armando Carteni, Luca D'Acierno, Mariano Gallo
Article
Chemistry, Multidisciplinary
Marilisa Botte, Mariano Gallo, Mario Marinelli, Luca D'Acierno
APPLIED SCIENCES-BASEL
(2020)
Article
Energy & Fuels
Mariano Gallo, Marilisa Botte, Antonio Ruggiero, Luca D'Acierno
Article
Engineering, Electrical & Electronic
Marilisa Botte, Luca D'Acierno, Mario Pagano
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2020)
Article
Green & Sustainable Science & Technology
Luca D'Acierno, Marilisa Botte
Summary: This paper focuses on modeling frequency-based public transport systems using the Merry-Go-Round paradigm and investigating the role of terminal station layout within this framework. The proposed formulation was implemented in a real-scale metro line to demonstrate its effectiveness.
Article
Engineering, Civil
Marilisa Botte, Amedeo Zampi, Cristina Oreto, Luca D'Acierno
Summary: The use of Building Information Modelling (BIM) is increasingly being adopted worldwide to support the creation and management of digital environments. In the infrastructure sector, BIM's flexibility and interoperability allow it to be implemented for optimizing traffic flow through traffic control plan design. By conducting a comprehensive analysis of infrastructure design, building issues, and transportation theory principles, a comparative analysis of two different BIM tool approaches is proposed.
JOURNAL OF ADVANCED TRANSPORTATION
(2021)
Article
Green & Sustainable Science & Technology
Luca D'Acierno, Matteo Tanzilli, Chiara Tescione, Luigi Pariota, Luca Di Costanzo, Salvatore Chiaradonna, Marilisa Botte
Summary: Sustainable transport frameworks are gaining attention in national and international transportation policies. This study compares the environmental impacts of different transport modes, including CO2 emissions, total costs, and service life of vehicles, to make urban environments more people-friendly.
Article
Engineering, Electrical & Electronic
Marilisa Botte, Luca D'Acierno, Antonio Di Pasquale, Fabio Mottola, Mario Pagano
Summary: The operators of the railway industry are currently undergoing a significant energy transition to improve environmental sustainability and energy efficiency. This entails updating technological infrastructures and studying new operating solutions. Furthermore, the operators are searching for power quality solutions due to the business opportunities in the new rail market.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2023)
Proceedings Paper
Computer Science, Information Systems
Marilisa Botte, Antonio Santonastaso, Luca D'Acierno
Summary: The paper presents a methodology for optimizing rail service operations to satisfy mobility demand while complying with current regulations. It demonstrates the effectiveness of the proposed method through its application on a real regional rail line in southern Italy.
ADVANCED INFORMATION NETWORKING AND APPLICATIONS, AINA-2022, VOL 3
(2022)
Proceedings Paper
Green & Sustainable Science & Technology
Luca D'Acierno, Loris Caldoro, Luigi Pariota, Luca Di Costanzo, Ilaria Henke, Marilisa Botte
Summary: This paper investigates the impact of micro-mobility solutions on student accessibility. By applying the solution in university plexuses in Naples, the study demonstrates that it increases the accessibility level and is preferred by users as a first/last mile option and an alternative to walking trips. Additionally, the proposed method proves to be effective as a Decision Support System.
2022 IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2022 IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC / I&CPS EUROPE)
(2022)
Proceedings Paper
Engineering, Electrical & Electronic
Marilisa Botte, Luca D'Acierno, Antonio Di Pasquale, Fabio Mottola, Mario Pagano
Summary: This paper discusses the optimal management of a fleet of metro trains in terms of power key performance indicator (KPI) and presents a numerical application focused on the traction power system of Metro Line 1 of Naples (Italy), highlighting the evaluation of power peaks required to the distribution grid as a function of Layover time assignment.
2021 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC)
(2021)
Proceedings Paper
Engineering, Electrical & Electronic
Francesco Apicella, Luigi Pariota, Luca Di Costanzo, Nicola Amatucci, Marilisa Botte, Luca D'Acierno, Pasquale Rovito, Andrea Vitiello, Erika Fusco
Summary: The development of smart cities relies on information and communication technologies, sustainable solutions, and innovative mobility frameworks. Utilizing the Internet of Things allows everyday objects to become computing devices that exchange useful data. This paper suggests using IoT for monitoring railway systems to gather information on service performance and travelers' behavior, showcasing the feasibility of the proposed methodology through a numerical application in a real rail context.
2021 21ST IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2021 5TH IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC/I&CPS EUROPE)
(2021)
Proceedings Paper
Engineering, Electrical & Electronic
Andrea Di Maio, Marilisa Botte, Bruno Montella, Luca D'Acierno
2020 20TH IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2020 4TH IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC/I&CPS EUROPE)
(2020)
Proceedings Paper
Engineering, Electrical & Electronic
Mariano Gallo, Antonio Ruggiero, Marilisa Botte, Luca D'Acierno
2020 20TH IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2020 4TH IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC/I&CPS EUROPE)
(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)
