Review
Management
Zehranaz Donmez, Bahar Y. Kara, Ozlem Karsu, Francisco Saldanha-da-Gama
Summary: This paper provides a comprehensive review of research on facility location problems under uncertainty in a humanitarian context, with a focus on different perspectives such as facility types, decision-making, optimization criteria, uncertainty capturing methods, and solution methods. The detailed analysis helps identify distinguishing features of the problems and current research trends, expectations, and gaps in existing knowledge, highlighting relevant research directions.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Management
Renata Turkes, Kenneth Sorensen, Daniel Palhazi Cuervo
Summary: Facility planning is a crucial decision for humanitarian managers. Existing literature often derives implications simply from sensitivity analysis on individual instance characteristics, neglecting important interactions between various disaster properties, which can be misleading. This study conducts a large experimental analysis to examine the influence of different factors and their interactions on facility configuration choices for emergency preparedness. The findings provide insights on the impact of significant factor interactions on facility decision-making and highlight the need for more robust experimental designs in humanitarian logistics.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Linlin Zhang, Na Cui
Summary: This study proposes a scenario-based stochastic program model to consider victims' welfare loss in disaster relief logistics. A case study demonstrates the importance of this model in humanitarian relief logistics.
Article
Management
Douglas Alem, Hector F. Bonilla-Londono, Ana Paula Barbosa-Povoa, Susana Relvas, Deisemara Ferreira, Alfredo Moreno
Summary: This study introduces a novel humanitarian supply chain approach to address disaster preparedness and response capacity in Brazil, where disasters are often linked with unequal opportunities and social inequalities. By developing an optimization model that incorporates the Social Vulnerability Index (SoVI), the study shows the importance of designing more socially-effective humanitarian supply chains, especially in areas with higher vulnerability.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Operations Research & Management Science
Levent Eriskin, Mumtaz Karatas
Summary: This study addresses the problem of shelter location and allocation under demand uncertainty, aiming to enhance the disaster preparedness level in Turkey. By utilizing a robust optimization approach, the study develops a model that considers the uncertainties in seismic parameters and urban vulnerability. The proposed formulation outperforms deterministic and stochastic counterparts, resulting in socially more acceptable and preferable solutions.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Renata Turkes, Kenneth Sorensen, Daniel Palhazi Cuervo
Summary: The paper presents a matheuristic approach to solve the stochastic facility location problem, optimizing the storage facility configuration to minimize unmet demand and response time. Numerical experiments show the effectiveness and efficiency of the method, particularly for tackling larger instances.
JOURNAL OF HEURISTICS
(2021)
Article
Geosciences, Multidisciplinary
Elif Yoruk, Adil Baykasoglu, Mualla Gonca Avci
Summary: One of the new pre-disaster activities in Turkiye is to locate neighborhood disaster stations for efficient relief item distribution. This study focuses on the location and replenishment problems of these disaster stations, as no previous research has considered both simultaneously. A MILP model is developed to minimize the maximum distance between post-disaster assembly areas and the nearest disaster station, while also minimizing transportation costs for replenishment.
Article
Economics
Giuseppe Timperio, Tanmoy Kundu, Matthias Klumpp, Robert de Souza, Xiu Hui Loh, Kelvin Goh
Summary: The growing frequency, impact, and complexity of natural and human-made disasters have led to increased attention towards humanitarian logistics management practices. This study proposes a multi-method decision support framework to analyze and optimize supply networks, addressing the key challenge of resource coordination in disaster response operations. The real-world application to the DELSA network demonstrates significant improvements in service level through the introduction of beneficiary-centric policies.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Geosciences, Multidisciplinary
Rhiannon A. D. G. E. Blanchette, Egid M. van Bree, Joost J. L. M. Bierens
Summary: Despite having a good healthcare system, recent studies have shown that the Netherlands struggles with hospital disaster preparedness. The lack of formal requirements for hospital disaster preparedness plans and the evaluation framework in the country may be contributing factors. This study aimed to evaluate the preparedness of Dutch hospitals by using the WHO Hospital Emergency Response Checklist. Results showed that none of the participating hospitals achieved an effective preparedness score and there was a significant variability in the configuration of the studied plans.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2023)
Article
Geosciences, Multidisciplinary
Su Nguyen, Greg O'Keefe, Sobhan Arisian, Kerry Trentelman, Damminda Alahakoon
Summary: This study examines the potential of AI-enabled wargames to enhance strategic decision making in humanitarian assistance and disaster relief scenarios. The researchers introduce a framework called ACTION, which uses a genetic programming algorithm to evolve intelligent and interpretable player policies. Experimental results show that the framework can adapt to uncertainties and adversarial actions. The study offers practical guidelines for improving logistics planning in humanitarian aid.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2023)
Article
Management
O. Baturhan Bayraktar, Dilek Gunnec, F. Sibel Salman, Eda Yucel
Summary: This article introduces the multi-period facility location problem on mobile facilities for aiding refugee groups, aiming to minimize setup and travel costs while ensuring service requirement. The authors propose a mixed integer linear programming model and develop an adaptive large neighborhood search algorithm to solve large-scale instances. By testing the data from the 2018 Honduras Migration Crisis, the effectiveness of the algorithm is demonstrated.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Economics
Francisco Saldanha-da-Gama
Summary: This article aims to contribute to the celebration of the 25th Anniversary of Transportation Research Part E: Logistics and Transportation Review by providing an overview of the role of Facility Location in Logistics and Transportation. It discusses the increasing importance of Facility Location due to technological developments, economy globalization, and environmental concerns. The article also explores current trends and future challenges, including the transition from Industry 4.0 to Industry 5.0 and the impact of data-driven decision making in the era of big data.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Management
Kanglin Liu, Changchun Liu, Xi Xiang, Zhili Tian
Summary: This paper focuses on locating testing facilities to meet varying demand caused by pandemics. A two-phase optimization framework is proposed to locate facilities and adjust capacity during emergencies. Online convex optimization and online gradient descent algorithms are used to solve the problem. A case study verifies the effectiveness of the framework.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Hardware & Architecture
Annunziata Esposito Amideo, Maria Paola Scaparra, Antonio Sforza, Claudio Sterle
Summary: This paper focuses on two crucial operations, shelter location determination and evacuation of endangered populations during disaster response phase, and presents the SISLER model for solving them. The results of the study provide useful managerial insights for relevant stakeholders.
Article
Green & Sustainable Science & Technology
Maria Rossana D. de Veluz, Anak Agung Ngurah Perwira Redi, Renato R. Maaliw, Satria Fadil Persada, Yogi Tri Prasetyo, Michael Nayat Young
Summary: The demand for humanitarian supply chains is increasing due to the rise in calamities. This paper proposes a stochastic model for creating a humanitarian network for pre-disaster response. The model aims to minimize costs, travel time, and vehicle requirements in transferring affected individuals to evacuation centers. The model was implemented in an actual scenario in the Philippines and solved using Multi-Objective Particle Swarm Optimization.
Article
Management
Ahmet Cinar, F. Sibel Salman, Burcin Bozkaya
Summary: The study focuses on how a nurse can prioritize patients for home visits based on factors such as last visit time and severity of condition. The goal is to maximize the total priority of visited patients and minimize traveling time. Results show that the matheuristic outperforms ALNS in large instances, although ALNS has shorter running times.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Software Engineering
Refael Hassin, R. Ravi, F. Sibel Salman, Danny Segev
Article
Management
Seren Bilge Yilmaz, Eda Yucel
Summary: Airlines provide complimentary or for-purchase in-flight meals, which are ideally loaded immediately before the flight. To minimize costs, they determine catering loading sites based on flight plan and estimated consumption for each flight.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Operations Research & Management Science
Davood Shiri, Vahid Akbari, F. Sibel Salman
Article
Management
Meraj Ajam, Vahid Akbari, Sibel Salman
Summary: After a disaster, it is crucial to restore blocked roads to enable relief efforts. This study proposes algorithms to determine the schedule and routes of multiple work teams, with the goal of minimizing the latency of reaching critical locations. Coordination among teams is essential, and heuristic methods are developed to handle the coordination requirement. The results show the superiority of solutions obtained by incorporating coordination.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Economics
Vahid Akbari, Davood Shiri, F. Sibel Salman
Summary: This article studies post-disaster road restoration problem, analyzing the performance of online algorithms against offline optimal solutions using competitive ratio. An optimal online algorithm is proposed, utilizing mixed integer programming model and a novel polynomial time online algorithm, showing superior performance in experiments.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Management
Eda Yucel, F. Sibel Salman, Gunes Erdogan
Summary: This paper introduces a multi-period, two-dimensional vehicle loading and dispatching problem, aiming to minimize the total vehicle usage and earliness penalty costs, and provides a Mixed-Integer Linear Programming model (MILP) and an Adaptive Large Neighbourhood Search (ALNS) algorithm for solving the problem.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Management
O. Baturhan Bayraktar, Dilek Gunnec, F. Sibel Salman, Eda Yucel
Summary: This article introduces the multi-period facility location problem on mobile facilities for aiding refugee groups, aiming to minimize setup and travel costs while ensuring service requirement. The authors propose a mixed integer linear programming model and develop an adaptive large neighborhood search algorithm to solve large-scale instances. By testing the data from the 2018 Honduras Migration Crisis, the effectiveness of the algorithm is demonstrated.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Mahdi Mostajabdaveh, F. Sibel Salman, Nadia Tahmasbi
Summary: This study addresses a two-dimensional cutting stock problem combined with production scheduling in the paper printing industry. The researchers propose a nonlinear integer programming model and a genetic algorithm to solve the problem, and also design a packing routine to generate balanced printing patterns. Computational experiments on large-scale real-world data demonstrate the efficiency of the genetic algorithm.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Operations Research & Management Science
Vahid Akbari, Ihsan Sadati, F. Sibel Salman, Davood Shiri
Summary: We study a problem of home healthcare routing and scheduling, where healthcare provider teams need to visit a set of patients at their homes. The problem aims to assign patients to teams and generate routes so that each patient is visited once. By prioritizing patients based on severity or urgency, the problem minimizes patients' waiting time, considering triage levels as weights. To solve this problem, we propose an integer programming model and a metaheuristic algorithm. The models are evaluated on different instances, and the algorithm achieves optimal solutions within seconds for all instances. A case study on Covid-19 patients in Istanbul provides insights for planners through various analyses.
Article
Business
Ahmet Cinar, F. Sibel Salman, Ozgur M. Araz, Mert Parcaoglu
Summary: In this article, we propose a reoptimization framework to address the dynamic problem of home healthcare during a public health emergency. The framework aims to maximize the total priority of visited patients, minimize the overtime for healthcare providers, and reduce the total routing time. By formulating a mixed-integer programming model, we periodically determine the order of patient visits on each day to ensure urgent patients are visited within the current day while postponing visits of other patients if necessary. The effectiveness of the schedule is evaluated based on metrics such as the number of postponed visits, waiting time of urgent patients, and required overtime. The proposed approach is compared with practical heuristics in a nervous service system, showcasing its efficacy during the COVID-19 pandemic.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2022)
Article
Computer Science, Interdisciplinary Applications
Umut Ermagan, Baris Yildiz, F. Sibel Salman
Summary: This study introduces a learning-based algorithm to solve the drone routing problem, which shows promising performance in experiments.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Computer Science, Hardware & Architecture
D. Shiri, F. S. Salman
IBM JOURNAL OF RESEARCH AND DEVELOPMENT
(2020)
Article
Management
Ozgur M. Araz, Tsan-Ming Choi, David L. Olson, F. Sibel Salman
Article
Management
Ozgur Merih Araz, Tsan-Ming Choi, David L. Olson, F. Sibel Salman
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)
