Article
Management
Vitor Notini Pontes, Dilson Lucas Pereira
Summary: Logistics problems are crucial in industries and a main point in operational research. The recent focus has been on workforce scheduling and routing problems (WSRP), particularly the multiperiod WSRP with dependent tasks. Two matheuristic algorithms were proposed, along with the discovery of new upper bounds for a set of instances.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2022)
Article
Automation & Control Systems
Nastaran Oladzad-Abbasabady, Reza Tavakkoli-Moghaddam, Mehrdad Mohammadi, Behdin Vahedi-Nouri
Summary: A Home Health Care Routing and Scheduling Problem (HHCRSP) is investigated with both soft and hard time windows associated with caregivers and patients. Five different types of soft temporal dependency constraints are considered, and a bi-objective Mixed-Integer Programming (MIP) model is devised to incorporate staff rostering, vehicle routing, and scheduling simultaneously. Computational results highlight the efficiency of the employed Iterated Local Search (ILS) algorithm compared to the Non-dominated Sorting Genetic Algorithm (NSGA-II).
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Yoram Clapper, Joost Berkhout, Rene Bekker, Dennis Moeke
Summary: This paper presents a model-based evolutionary algorithm for the Home Health Care Routing and Scheduling Problem (HHCRSP). The algorithm generates routes with care activities and shift schedules, considering qualification levels. Performance is optimized in terms of travel time, time window waiting time, and shift overtime. Numerical experiments using real-life data show close-to-optimal performance for small instances and a 41% efficiency gain compared to a case study. Furthermore, the model-based evolutionary algorithm outperforms a traditional evolutionary algorithm, emphasizing the importance of learning and exploiting a model in HHCRSP optimization.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Shaojun Chen, Xiaoqing Wu, Jing Wu, Xueqing Hong
Summary: This paper investigates the home-based elderly care program under uncertainty by considering the costs of care such as fixed costs, time, and transportation costs. A deterministic mixed integer programming model is constructed to solve the general routing scheduling problem. Robust optimization theory and algorithm models are introduced to handle the uncertainty and risk in the market. The results show that the deterministic model has the lowest cost under certain conditions, but the robust optimization models achieve more robust home-based elderly care programs under uncertain conditions.
Article
Economics
Ana Raquel Pena de Aguiar, Tania Rodrigues Pereira Ramos, Maria Isabel Gomes
Summary: The demand for home care services is growing steadily, especially in healthcare and social care. This study focuses on the synchronization of caregivers in social care services to improve human resources management. It introduces decision support tools to assist managers in designing operational plans and efficiently assigning caregivers to tasks. By considering teams of one caregiver that can synchronize to perform tasks requiring two caregivers, daily continuity of care and teams' synchronization can be effectively modeled.
SOCIO-ECONOMIC PLANNING SCIENCES
(2023)
Article
Economics
Delaram Pahlevani, Babak Abbasi, John W. Hearne, Andrew Eberhard
Summary: This paper presents a mixed-integer linear programming model for routing and scheduling problems in home health care (HHC), aiming to achieve fair and balanced workload allocation of caregivers while minimizing total costs and addressing client needs. To address the complexity of the problem, a multi-steps clustering approach is employed to solve the model.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Computer Science, Artificial Intelligence
Sina Shahnejat-Bushehri, Reza Tavakkoli-Moghaddam, Mehdi Boronoos, Ahmad Ghasemkhani
Summary: This paper introduces a robust optimization model for home health care routing-scheduling problem with uncertain service and travel times, utilizing three meta-heuristic algorithms to solve the issue. Experimental results indicate that the memetic algorithm performs better for large-sized problems, demonstrating the advantage of using a robust model.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Management
Roberto Aringhieri, Davide Duma, Paolo Landa, Simona Mancini
Summary: This paper develops a solution approach for operating room planning and scheduling that takes into account both patient priority maximisation and workload balance. By proposing a new class of algorithms, better solutions can be generated in a shorter running time, and the quality of the solutions is evaluated through quantitative analysis.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Maria Di Mascolo, Clea Martinez, Marie-Laure Espinouse
Summary: This paper provides a literature survey on the problems of routing and scheduling in Home Health Care, highlighting the constraints and objectives, as well as discussing current trends with a focus on uncertain and dynamic aspects, and future research directions.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Oncology
Tugba Ulgen, Ozlem Ugur
Summary: This study investigated the impact of home care practices and perceived social support level on the burden of care for caregivers of cancer patients, finding that increased home care practices and decreased social support level can lead to an increase in caregiver burden.
SUPPORTIVE CARE IN CANCER
(2022)
Article
Engineering, Manufacturing
Andre A. Cire, Adam Diamant
Summary: This study proposes a dynamic scheduling framework for assigning health practitioners to patients in home care. By using approximate dynamic programming, four policies are compared, and the results of a simulation study show that accounting for future uncertainty leads to cost savings and fewer referrals.
PRODUCTION AND OPERATIONS MANAGEMENT
(2022)
Article
Computer Science, Information Systems
Ji Li, Huagang Xiong, Qiao Li, Feng Xiong, Jiaying Feng
Summary: This paper presents a joint mapping, routing, and scheduling reconfiguration method (JILP) based on integer linear programming for time-triggered networks. By introducing scheduling compatibility and a novel heuristic algorithm (SCA), the reconfiguration time is reduced and the experimental results show that JILP has a higher success rate compared to other algorithms.
Article
Computer Science, Interdisciplinary Applications
Gang Du, Jingjing Zhang
Summary: Home health care services supply is insufficient and unbalanced in China, especially in terms of elderly nursing manpower. It is crucial to arrange the existing nursing personnel in a reasonable manner to fully utilize their service capabilities.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Review
Operations Research & Management Science
Jalel Euchi, Malek Masmoudi, Patrick Siarry
Summary: This literature review provides a description and taxonomy of the problem of home health services. It summarizes the state-of-the-art decision-making solutions for the routing and scheduling problem in home health care, and examines related objectives and constraints.
4OR-A QUARTERLY JOURNAL OF OPERATIONS RESEARCH
(2022)
Article
Health Care Sciences & Services
Marianne Saragosa, Sonia Nizzer, Sandra McKay, Kerry Kuluski
Summary: This study provides insight into the care transition experiences and perspectives of home care clients and caregivers who have experienced a hospital-to-home transition. The findings highlight the importance of interactions with the health system, barriers in the system, facilitators to positive transitions, and emotional impact.
BMC HEALTH SERVICES RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Rafael Praxedes, Teobaldo Bulhoes, Anand Subramanian, Eduardo Uchoa
Summary: The Vehicle Routing Problem with Simultaneous Pickup and Delivery is a classical optimization problem that aims to determine the least-cost routes while meeting pickup and delivery demands and vehicle capacity constraints. In this study, a unified algorithm is proposed to solve multiple variants of the problem, and extensive computational experiments are conducted to evaluate the algorithm's performance.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Ragheb Rahmaniani, Teodor Gabriel Crainic, Michel Gendreau, Walter Rei
Summary: Benders decomposition (BD) is a popular solution algorithm for stochastic integer programs. However, existing parallelization methods often suffer from inefficiencies. This paper proposes an asynchronous parallel BD method and demonstrates its effectiveness through numerical studies and performance enhancement strategies.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Giulia Caselli, Maxence Delorme, Manuel Iori, Carlo Alberto Magni
Summary: This study addresses a real-world scheduling problem and proposes four exact methods to solve it. The methods are evaluated through computational experiments on different types of instances and show competitive advantages on specific subsets. The study also demonstrates the generalizability of the algorithms to related scheduling problems with contiguity constraints.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Shaowen Yao, Chao Tang, Hao Zhang, Songhuan Wu, Lijun Wei, Qiang Liu
Summary: This paper examines the problem of two-dimensional irregular multiple-size bin packing and proposes a solution that utilizes an iteratively doubling binary search algorithm to find the optimal bin combination, and further optimizes the result through an overlap minimization approach.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Decheng Wang, Ruiyou Zhang, Bin Qiu, Wenpeng Chen, Xiaolan Xie
Summary: Consideration of driver-related constraints, such as mandatory work break, in vehicle scheduling and routing is crucial for safety driving and protecting the interests of drivers. This paper addresses the drop-and-pull container drayage problem with flexible assignment of work break, proposing a mixed-integer programming model and an algorithm for solving realistic-sized instances. Experimental results show the effectiveness of the proposed algorithm in handling vehicle scheduling and routing with work break assignment.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
William N. Caballero, Jose Manuel Camacho, Tahir Ekin, Roi Naveiro
Summary: This research provides a novel probabilistic perspective on the manipulation of hidden Markov model inferences through corrupted data, highlighting the weaknesses of such models under adversarial activity and emphasizing the need for robustification techniques to ensure their security.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Davood Zaman Farsa, Shahryar Rahnamayan, Azam Asilian Bidgoli, H. R. Tizhoosh
Summary: This paper proposes a multi-objective evolutionary framework for compressing feature vectors using deep autoencoders. The framework achieves high classification accuracy and efficient image representation through a bi-level optimization scheme. Experimental results demonstrate the effectiveness and efficiency of the proposed framework in image processing tasks.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Matthew E. Scherer, Raymond R. Hill, Brian J. Lunday, Bruce A. Cox, Edward D. White
Summary: This paper discusses instance generation methods for the multidemand multidimensional knapsack problem and introduces a primal problem instance generator (PPIG) to address feasibility issues in current instance generation methods.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Yin Yuan, Shukai Li, Lixing Yang, Ziyou Gao
Summary: This paper investigates the design of real-time train regulation strategies for urban rail networks to reduce train deviations and passenger waiting times. A mixed-integer nonlinear programming (MINLP) model is used and an efficient iterative optimization (IO) approach is proposed to address the complexity. The generalized Benders decomposition (GBD) technique is also incorporated. Numerical experiments show the effectiveness and computational efficiency of the proposed method.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Xinghai Guo, Netirith Narthsirinth, Weidan Zhang, Yuzhen Hu
Summary: This study proposes a bi-level scheduling method that utilizes unmanned surface vehicles for container transportation. By formulating mission decision and path control models, efficient container transshipment and path planning are achieved. Experimental results demonstrate the effectiveness of the proposed approach in guiding unmanned surface vehicles to complete container transshipment tasks.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Review
Computer Science, Interdisciplinary Applications
Jose-Fernando Camacho-Vallejo, Carlos Corpus, Juan G. Villegas
Summary: This study aims to review the published papers on implementing metaheuristics for solving bilevel problems and performs a bibliometric analysis to track the evolution of this topic. The study provides a detailed description of the components of the proposed metaheuristics and analyzes the common combinations of these components. Additionally, the study provides a detailed classification of how crucial bilevel aspects of the problem are handled in the metaheuristics, along with a discussion of interesting findings.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Xudong Diao, Meng Qiu, Gangyan Xu
Summary: In this study, an optimization model for the design of an electric vehicle-based express service network is proposed, considering limited recharging resources and power management. The proposed method is validated through computational experiments on realistic instances.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Ramon Piedra-de-la-Cuadra, Francisco A. Ortega
Summary: This study proposes a procedure to select candidate sites optimally for ensuring energy autonomy and reinforced service coverage for electric vehicles, while considering demand and budget restrictions.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Danny Blom, Christopher Hojny, Bart Smeulders
Summary: This paper focuses on a robust variant of the kidney exchange program problem with recourse, and proposes a cutting plane method for solving the attacker-defender subproblem. The results show a significant improvement in running time compared to the state-of-the-art, and the method can solve previously unsolved instances. Additionally, a new practical policy for recourse is proposed and its tractability for small to mid-size kidney exchange programs is demonstrated.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Anqi Li, Congying Han, Tiande Guo, Bonan Li
Summary: This study proposes a general framework for designing linear programming instances based on the preset optimal solution, and validates the effectiveness of the framework through experiments.
COMPUTERS & OPERATIONS RESEARCH
(2024)
