Article
Computer Science, Artificial Intelligence
Simon Caillard, Laure Brisoux Devendeville, Corinne Lucet
Summary: In this paper, two ant algorithms (AS and ACS) are proposed to solve a planning problem in the Health Simulation Center SimUSante. Experimental results show that SimU-TACS outperforms other methods and provides optimal solutions for 31/48 instances.
APPLIED SOFT COMPUTING
(2023)
Article
Operations Research & Management Science
Arjan Akkermans, Gerhard Post, Marc Uetz
Summary: This paper introduces a two-phase approach using integer linear programming to solve the shift and break design problem. The approach creates shifts while considering breaks heuristically in the first phase, and assigns breaks to shifts in the second phase until no improvement is found. Results show that this approach outperforms the current best known method for shift and break design problem on a set of benchmark instances.
ANNALS OF OPERATIONS RESEARCH
(2021)
Article
Management
Rasul Esmaeilbeigi, Vicky Mak-Hau, John Yearwood, Vivian Nguyen
Summary: This paper investigates the multiphase course timetabling problem and proposes mathematical formulations and effective solution algorithms. The study extends the model by introducing additional constraints and presents an enhanced algorithm. Computational results demonstrate the efficacy of the proposed algorithms.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Ziyi Chen, Yajie Dou, Patrick De Causmaecker
Summary: This study proposes a neural network-assisted method for addressing the complex nurse scheduling problem, and it demonstrates good performance in experiments.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Transportation Science & Technology
Xiaoming Xu, Yanhong Yu, Jiancheng Long
Summary: Vehicle timetabling and scheduling in a public transit system are usually performed separately, resulting in a lack of trade-off between bus timetables and vehicle schedules. This paper proposes an integrated framework for electric bus timetabling and scheduling, considering various factors such as headway times, depot requirements, deadheading, and vehicle battery capacities. A time-space network is constructed with inventory arcs to decrease the network size, and a multi-commodity network flow model is formulated. Through a Lagrangian relaxation heuristic, the proposed method efficiently produces bus timetables and schedules with improved profit and valid bounds.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Computer Science, Artificial Intelligence
Simon Caillard, Laure Brisoux Devendeville, Corinne Lucet
Summary: The paper introduces the Variable Neighborhood Search (VNS) algorithm SimULS to solve a planning problem in the Health Simulation Center SimUSante. The algorithm combines different neighborhood functions and uses a diversification function when trapped in a local optimum. Experimental results show that SimULS is able to schedule all activities without violating constraints, providing solutions close to the optimum.
APPLIED INTELLIGENCE
(2022)
Article
Management
T. Breugem, B. T. C. van Rossum, T. Dollevoet, D. Huisman
Summary: The paper proposes a novel integrated approach for crew re-planning in response to changes in the timetable and rolling stock schedule. This approach allows for more flexibility compared to current practices, considering the feasibility of rosters while solving crew re-planning in a simultaneous manner.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2022)
Article
Energy & Fuels
Hubert Maximilian Sistig, Dirk Uwe Sauer
Summary: Driven by global and local environmental concerns, public transport operators are transitioning to battery-powered electric buses. The total cost of ownership is the most crucial factor in choosing the electric bus concept. This paper analyzes the relationship between electrification and operational planning, focusing on vehicle scheduling and crew scheduling.
Article
Economics
Xin Wen, Xuting Sun, Yige Sun, Xiaohang Yue
Summary: This paper reviews the literature on airline crew scheduling problems from four aspects: scheduling for cabin crew, scheduling for both cabin crew and cockpit crew, robust scheduling for cockpit crew, and recovery for cockpit crew. By examining multiple prior studies, advancements in model development and solution algorithm construction were reviewed to provide insights. Future research agenda for the airline crew scheduling problem is proposed as a conclusion to the review.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2021)
Article
Computer Science, Artificial Intelligence
Victor M. Valenzuela-Alcaraz, M. A. Cosio-Leon, A. Danisa Romero-Ocano, Carlos A. Brizuela
Summary: The study proposes a cooperative coevolutionary algorithm for solving the no-wait job shop scheduling problem. The algorithm evolves permutations and binary chains simultaneously to optimize sequencing and timetabling decisions, and includes one-step perturbation mechanisms to improve solution quality. Experimental results show that the proposed algorithm produces competitive results and obtains new best values for some instances.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Biology
Asaju La'aro Bolaji, Akeem Femi Bamigbola, Lawrence Bunmi Adewole, Peter Bamidele Shola, Adenrele Afolorunso, Adesoji Abraham Obayomi, Dayo Reuben Aremu, Abdulwahab Ali A. Almazroi
Summary: This paper proposes an Artificial Bee Colony Algorithm (ABC) to solve the Patient Admission Scheduling (PAS) problem. The performance evaluation of the ABC algorithm on the PAS reveals its superiority compared to other methods.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Computer Science, Information Systems
Emiliana Mara Lopes Simoes, Lucas De Souza Batista, Marcone Jamilson Freitas Souza
Summary: This work addresses the multiple-depot vehicle and crew scheduling problem in public bus transport systems, proposing a matheuristic algorithm that combines branch-and-bound and variable neighborhood descent algorithms. The results show the algorithm's effectiveness in solving real-world and large-scale problems, outperforming existing approaches in the literature.
Article
Computer Science, Interdisciplinary Applications
Vivian Nguyen, Vicky Mak-Hau, Bill Moran, Ana Novak
Summary: The algorithm efficiently and accurately schedules and optimally assigns military trainees to classes, respecting domain constraints. It shows significant computational benefit compared to other methods and can handle larger-scale problems effectively.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Operations Research & Management Science
Intesar Al-Mudahka, Reem Alhamad
Summary: This paper proposes a mathematical goal program for designing timetables for radiologists, which simplifies the process and promotes efficiency and fairness. The program can be used at both the strategic and operational levels to meet different needs.
RAIRO-OPERATIONS RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
M. Cildoz, F. Mallor, P. M. Mateo
Summary: This paper addresses a physician scheduling problem in an Emergency Room using a mathematical model that combines linear programming with a greedy randomized adaptive search procedure. The approach outperforms traditional methods in generating schedules for a local ER, resulting in improved efficiency and effectiveness.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Interdisciplinary Applications
Andres Gutierrez, Laurence Dieulle, Nacima Labadie, Nubia Velasco
COMPUTERS & OPERATIONS RESEARCH
(2018)
Article
Computer Science, Information Systems
Fabian Castano, Andre Rossi, Marc Sevaux, Nubia Velasco
INFORMATION SCIENCES
(2018)
Article
Green & Sustainable Science & Technology
Gustavo A. Bula, H. Murat Afsar, Fabio A. Gonzalez, Caroline Prodhon, Nubia Velasco
JOURNAL OF CLEANER PRODUCTION
(2019)
Article
Management
Fabian Castano, Nubia Velasco
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2020)
Article
Energy & Fuels
Maria Acuna, Carlos Silva, Andres Tocaruncho, Diana Vargas, Diego Patino, David Barrera, Johan Pena
Summary: The article proposes a simulation-optimization framework to address the integrated energy dispatch and unit commitment problem for a solar radiation system in non-interconnected zones. The method is able to find good solutions in short computational times and handle the random nature of the process. It demonstrates practical use in a low-budget rural school setting.
Article
Engineering, Industrial
Juan Guiza, Rafael Luque, Jennifer Murillo, Rodrigo Romero, David Barrera, Hector Lopez-Ospina
Summary: This study investigates the integration between pricing and coordinated inventory decisions for a two-echelon supply chain in a competitive environment. A novel mathematical model is developed to coordinate inventory policies and determine selling prices using MNL demand functions, with three metaheuristics implemented to solve the resulting discrete-continuous problem. Computational experiments demonstrate the economic benefits of the integrated approach.
JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING
(2021)
Article
Multidisciplinary Sciences
David Barrera Ferro, Steffen Bayer, Laura Bocanegra, Sally Brailsford, Adriana Diaz, Elena Valentina Gutierrez-Gutierrez, Honora Smith
Summary: This study investigates the reasons for no-show behavior for cervical cancer screening appointments among low-income women in Bogota, Colombia. The quantitative analysis reveals that younger patients and those living in poverty are more likely to miss their appointments. The qualitative analysis shows that patients encounter difficulties in navigating the service delivery process, accessing the health system, and hold negative beliefs about cervical cytology.
Article
Public, Environmental & Occupational Health
David Barrera Ferro, Steffen Bayer, Sally Brailsford, Honora Smith
Summary: The study combines machine learning methods and Champion's Health Belief Model to assess factors influencing women's participation in cervical cancer screening. Results show that lower income patients have lower health motivation scores, higher barrier scores, and patients who are younger and in extreme poverty are less likely to attend appointments. This method has the potential to improve the cost-effectiveness of behavioral interventions in developing countries.
Article
Engineering, Industrial
Gabriela Chavarro, Matthaus Fresen, Esneyder Rafael Gonzalez, David Barrera Ferro, Hector Lopez-Ospina
Summary: This research focuses on the stochastic version of a two-echelon inventory system by designing an extension of a well-known heuristic, considering customer demands following a normal density function. Evaluation was conducted through generating 240 random instances and comparing deterministic and stochastic solution approaches. Computational experiments demonstrate that using average demand for inventory policy underestimates total cost, while the newly proposed method offers cost savings.
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING COMPUTATIONS
(2021)
Article
Management
Fabian Castano, Nubia Velasco
Summary: This paper proposes a mathematical model based on directed acyclic graphs to minimize personnel required for home health-care services. Results show efficient solutions for medium-sized instances up to 100 daily patient requests. The model allows for realistic characteristics and can be applied to other real-life applications.
INTERNATIONAL JOURNAL OF LOGISTICS MANAGEMENT
(2021)
Article
Computer Science, Artificial Intelligence
David Barrera Ferro, Sally Brailsford, Cristian Bravo, Honora Smith
DECISION SUPPORT SYSTEMS
(2020)
Editorial Material
Business
Nubia Milena Velasco, Gonzalo Mejia
ACADEMIA-REVISTA LATINOAMERICANA DE ADMINISTRACION
(2019)
Proceedings Paper
Automation & Control Systems
A. Felipe Torres-Ramos, Nacima Labadie, Nubia Velasco, Jairo R. Montoya-Torres
Article
Computer Science, Information Systems
F. Castano, N. Velasco, J. Carvajal-Beltran
IEEE LATIN AMERICA TRANSACTIONS
(2019)
Article
Business
Nubia Velasco, Juan-Pablo Moreno, Claudia Rebolledo
ACADEMIA-REVISTA LATINOAMERICANA DE ADMINISTRACION
(2018)
Article
Computer Science, Interdisciplinary Applications
Xiaolin Wang, Liyi Zhan, Yong Zhang, Teng Fei, Ming-Lang Tseng
Summary: This study proposes an environmental cold chain logistics distribution center location model to reduce transportation costs and carbon emissions. It also introduces a hybrid arithmetic whale optimization algorithm to overcome the limitations of the conventional algorithm.
COMPUTERS & INDUSTRIAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hong-yu Liu, Shou-feng Ji, Yuan-yuan Ji
Summary: This study proposes an architecture that utilizes Ethereum to investigate the production-inventory-delivery problem in Physical Internet (PI), and develops an iterative heuristic algorithm that outperforms other algorithms. However, due to gas prices and consumption, blockchain technology may not always be the optimal solution.
COMPUTERS & INDUSTRIAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Paraskevi Th. Zacharia, Elias K. Xidias, Andreas C. Nearchou
Summary: This article discusses the assembly line balancing problem in production lines with collaborative robots. Collaborative robots have the potential to improve automation, productivity, accuracy, and flexibility in manufacturing. The article explores the use of a problem-specific metaheuristic to solve this complex problem under uncertainty.
COMPUTERS & INDUSTRIAL ENGINEERING
(2024)
