Article
Operations Research & Management Science
Farshad Majzoubi, Lihui Bai, Sunderesh S. Heragu
Summary: The study focuses on the real-time emergency medical service vehicle patient transportation problem, and proposes a simulated annealing heuristic for high-quality solutions suitable for implementation in a real-time decision support system.
JOURNAL OF GLOBAL OPTIMIZATION
(2021)
Article
Computer Science, Interdisciplinary Applications
Nicolas Cabrera, Jean-Francois Cordeau, Jorge E. Mendoza
Summary: This paper introduces a highly efficient heuristic for the doubly open park-and-loop routing problem, which can generate high-quality solutions quickly.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Enrico Angelelli, Claudia Archetti, Carlo Filippi, Michele Vindigni
Summary: The study focuses on an online version of the orienteering problem, formulating it as a Markov Decision Process and testing various heuristic approaches. Extensive computational tests are conducted to discuss the pros and cons of the different methods.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Alberto Santini, Michael Schneider, Thibaut Vidal, Daniele Vigo
Summary: This paper fills the gap in the literature by discussing the characteristics of decomposition techniques in vehicle routing heuristics and investigating their impact on two algorithms for the capacitated vehicle routing problem. The results show that route-based decomposition methods generally outperform path-based methods, and the newly proposed decomposition barycenter clustering achieves the best performance.
INFORMS JOURNAL ON COMPUTING
(2023)
Article
Engineering, Industrial
Tingting Chen, Feng Chu, Jiantong Zhang, Jiaqing Sun
Summary: This study addresses the sustainability challenges in pharmaceutical refrigerated logistics by proposing collaborative strategies that improve logistics efficiency while promoting vehicle flow equilibrium at each depot, offering valuable insights for decision-makers in the market.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Review
Chemistry, Multidisciplinary
Shi-Yi Tan, Wei-Chang Yeh
Summary: Transportation planning, especially in the context of vehicle routing problems (VRPs), has become a significant area of research interest, with growing attention to real-life applications and evolving algorithms to tackle complex instances. This study provides a comprehensive analysis of recent literature on VRPs, categorizing models into customer-related, vehicle-related, and depot-related, and classifying solution algorithms as exact, heuristic, or meta-heuristic. It also introduces a valuable classification table as Appendix A for easy access to relevant literature and insight into the latest trends and methodologies in the field.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Interdisciplinary Applications
Pol Arias-Melia, Jiyin Liu, Rupal Mandania
Summary: This paper examines the problem of vehicle sharing and task allocation, proposing an integer programming model and a heuristic algorithm. Results show that sharing vehicles can save on vehicle usage and reduce carbon emissions.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Computer Science, Hardware & Architecture
Burak Boyaci, Thu Huong Dang, Adam N. Letchford
Summary: The general routing problem is an important NP-hard problem that has various special cases. This paper examines a known constructive heuristic for this problem and proposes improvements to accelerate the algorithm while obtaining better solutions.
Article
Economics
Inmaculada Rodriguez-Martin, Hande Yaman
Summary: This study extends the classic Vehicle Routing Problem by considering routes for multiple vehicles over a time horizon of several days. It also takes into account the visit schedules and service times of customers to maximize the utility of the service to the company.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Management
Konstantin Kloster, Mahdi Moeini, Daniele Vigo, Oliver Wendt
Summary: In this paper, the authors introduce the multiple Traveling Salesman Problem with Drone Stations (mTSP-DS), which extends the classical mTSP by incorporating the use of drones or robots stationed at packet stations. The goal is to serve all customers using trucks and drones while minimizing the makespan. The authors propose algorithms based on mixed integer linear programming model, decomposition-based matheuristic, and iterated local search metaheuristic to solve the problem. Computational experiments demonstrate that the use of drone stations leads to significant savings in delivery time compared to traditional solutions and can also achieve energy savings.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Florian Arnold, Kenneth Soerensen
Summary: This study introduces an efficient and effective heuristic for the LRP, which reduces the solution space by estimating an upper bound for the number of open depots and iteratively applying routing heuristic to each remaining depot configuration. The progressive filtering framework quickly detects unpromising configurations, and a good design combining coarse and fine filters outperforms existing heuristics on various instances.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Operations Research & Management Science
Munjeong Kang, Chungmok Lee
Summary: There are recent attempts to utilize drones in logistics, considering the collaboration between multiple drones with different characteristics and trucks in delivery services. A heterogeneous drone-truck routing problem is proposed, with a mixed-integer programming formulation and an exact algorithm based on logic-based Benders decomposition, outperforming current solvers.
TRANSPORTATION SCIENCE
(2021)
Article
Agriculture, Multidisciplinary
Heungjo An
Summary: This study proposes a novel method for solving the daily scheduling problem of trucks and mobile loaders in the biomass transportation system, aiming to reduce transportation costs and find feasible solutions in difficult cases.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Construction & Building Technology
Ugur Bac, Mehmet Erdem
Summary: The use of electric vehicles is increasing, but issues such as limited mileage and long recharging times hinder their widespread adoption in industrial and commercial logistics. Effective planning of EV routes and recharge schedules plays a crucial role in overcoming these obstacles.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Computer Science, Interdisciplinary Applications
Yibo Dang, Theodore T. Allen, Manjeet Singh
Summary: This paper addresses a heterogeneous vehicle routing problem with common carriers and time regulations and proposes the Red-Black Ant Colony System (RB-ACS) algorithm to solve the problem. The algorithm can simultaneously solve dedicated fleet routing and outsourcing decisions and achieve cost savings by improving bidding and outsourcing.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Operations Research & Management Science
Alexandre M. Florio, Richard F. Hartl, Stefan Minner, Juan-Jose Salazar-Gonzalez
Summary: This paper addresses the Vehicle Routing Problem with Stochastic Demands and Probabilistic Duration Constraints (VRPSD-PDC) and presents a solution using a novel branch-and-price algorithm. Computational experiments are conducted with different demand probability distributions and duration constraints levels. The optimal solutions may involve routes serving demands exceeding vehicle capacity, utilizing optimal restocking to reduce costs. Sensitivity analysis shows that high demand variability negatively affects the solution in terms of cost and number of routes.
TRANSPORTATION SCIENCE
(2021)
Article
Operations Research & Management Science
Jasmin Grabenschweiger, Karl F. Doerner, Richard F. Hartl, Martin W. P. Savelsbergh
Summary: By utilizing a system with alternative delivery points such as locker box stations, logistic efficiency and customer convenience can be improved while minimizing costs. The system allows customers to choose between home delivery and locker box pickup, offering compensation options and considering parcel sizes and slot availability. Mathematical formulation and metaheuristic solutions can help optimize the last-mile delivery process efficiently.
CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Alina G. Dragomir, Tom Van Woensel, Karl F. Doerner
Summary: Online second-hand marketplaces have experienced a significant increase in transactions, but private buyers and sellers in C2C settings may face inconveniences in sending and receiving parcels. This paper proposes a solution approach based on a multi-start, adaptive, large neighborhood search with problem specific operators to solve the pickup and delivery problem with alternative locations. By comparing with similar problems and analyzing real data, the study finds that increasing flexibility and convenience for customers can result in cost savings of up to 30% for carriers.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Management
David Wolfinger, Margaretha Gansterer, Karlf. Doerner, Nikolas Popper
Summary: This article addresses the logistics problem in COVID-19 testing, introduces the contagious disease testing problem (CDTP), and presents a solution. By optimizing the opening of test centers and routes of mobile test teams to minimize costs, the efficiency of public health response to pandemics can be improved.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Management
Ulrike Ritzinger, Jakob Puchinger, Christian Rudloff, Richard F. Hartl
Summary: Progress in digitalization provides opportunities for capturing transportation logistics data and improving decision support in transportation services. In this study, we propose different anticipatory algorithms for a dynamic and stochastic patient transportation problem and analyze their performance in a real-world application. The experimental results show that incorporating information about future requests enhances solution quality, and simple waiting strategies are most suitable for highly dynamic environments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Engineering, Industrial
Roland Braune, Frank Benda, Karl F. Doerner, Richard F. Hartl
Summary: This paper presents a Genetic Programming approach for solving flexible shop scheduling problems, generating priority rules for job dispatching and minimizing the makespan. Through testing on benchmark problem settings and a special industrial case, along with comparison between single-tree and multi-tree approaches, the study demonstrates consistent performance improvements over existing priority rules.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2022)
Article
Engineering, Industrial
Richard F. Hartl, Peter M. Kort, Stefan Wrzaczek
Summary: This paper studies the trade-off between durability and reputation for a firm, and analyzes the impact of government policy on firm decision making. The research finds that the length of warranty period, consumer awareness of warranty, and uncertainty about product breakdown all have effects on product lifetime.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Operations Research & Management Science
Margaretha Gansterer, Richard F. Hartl, Michal Tzur
Summary: Traditionally, there was a focus on owning resources, but now there is a trend towards sharing resources, especially in the transportation sector. Sharing resources can improve efficiency, reduce costs, and promote sustainability.
TRANSPORTATION SCIENCE
(2022)
Article
Management
Georg E. A. Froehlich, Margaretha Gansterer, Karl F. Doerner
Summary: This study reviews and categorizes literature on safe and secure vehicle routing problems and provides a starting point for researchers in this field. The study reveals that the majority of related articles have been published in the last five years and cover various aspects such as transportation of hazardous materials, patrol routing, cash-in-transit, dissimilar routing problems, and modeling of multi-graphs. The paper also discusses relevant methods and instances, along with identifying future research directions.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Article
Operations Research & Management Science
Gustav Feichtinger, Richard F. Hartl, Peter M. Kort, Andrea Seidl, Stefan Wrzaczek
Summary: This paper examines the impact of a firm's own capital stock and its competitor's capital stock on investment in a capital accumulation game. The study finds that if a firm acknowledges that its own capital stock increases the efficiency of the competitor's investments, the firm will invest less.
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
(2022)
Article
Computer Science, Interdisciplinary Applications
Emilio J. Alarcon Ortega, Karl F. Doerner
Summary: This article addresses a continuous-time variant of the inventory routing problem under stochastic demands. The problem at hand considers continuous decrease of inventory during the period due to customer demand. A two-stage mathematical program is formulated to manage replenishment decisions and reduce costs. An adaptive large neighborhood search algorithm is developed to find solutions, and the impact of using recourse actions to handle lost sales is evaluated. The algorithm's performance is compared with other algorithms from the literature, considering stochastic demands, and efficiency and levels of stochasticity are analyzed.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Management
Alexandre M. Florio, Michel Gendreau, Richard F. Hartl, Stefan Minner, Thibaut Vidal
Summary: This paper examines the stochastic variant of the Vehicle Routing Problem (VRP) called VRPSD, where demands are only revealed upon vehicle arrival at each customer. The paper summarizes recent progress in VRPSD research and introduces two major contributions: a branch-price-and-cut algorithm for optimal restocking and a demand model for correlated customer demands. Computational results demonstrate the effectiveness of the new algorithm and the potential cost savings of over 10% when considering demand correlation.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Management
J. P. Caulkins, D. Grass, G. Feichtinger, R. F. Hartl, P. M. Kort, M. Kuhn, A. Prskawetz, M. Sanchez-Romero, A. Seidl, S. Wrzaczek
Summary: This paper explores the variation of lockdown policies during the gap between vaccine approval and complete vaccination. The study finds that the intensity and duration of lockdowns may increase or decrease as the rate of vaccine deployment increases, depending on other model parameters. Vaccines and lockdowns can act as substitutes or complements, depending on the specific conditions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Hardware & Architecture
Georg E. A. Frohlich, Margaretha Gansterer, Karl F. Doerner
Summary: In this study, we propose a novel time-dependent multi-visit dynamic safe street snow plowing problem and develop an adaptive large neighborhood search method to solve it. By examining real-world-based instances for Vienna, we find that different snowstorm movements do not significantly affect the choice of rolling horizon settings. Our findings also suggest that larger updating intervals are beneficial when prediction errors are low, and larger look-aheads are better suited for larger updating intervals.
Article
Computer Science, Interdisciplinary Applications
Alexander Kinast, Roland Braune, Karl F. Doerner, Stefanie Rinderle-Ma, Christian Weckenborg
Summary: A hybrid genetic algorithm was proposed to solve the task shop scheduling problem with cobots allocation, demonstrating that deploying additional robots can significantly improve production efficiency.
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION
(2022)
