Review
Management
Claudia Archetti, Ivana Ljubic
Summary: This paper proposes an analysis and comparison of the strength of lower bound in different formulations for the Inventory Routing Problem (IRP). It investigates the equivalence between aggregated formulations and formulations with exponentially many constraints, as well as between aggregated and disaggregated formulations in terms of linear relaxation value. The analysis fills a research gap in the field of IRP and presents competitive exact solution approaches based on aggregated formulations.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Management
Agostinho Agra, Marielle Christiansen, Laurence Wolsey
Summary: This study addresses an inventory routing problem where a single vehicle transports goods from supply locations to demand locations. Two models are proposed and compared through computational tests using maritime transportation instances.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(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
Computer Science, Artificial Intelligence
Gozde Onder Uzun, Imdat Kara
Summary: The Traveling Repairman Problem (TRP) and its variant TRPTW focus on minimizing the total latency for all customers, with limited literature available. This paper proposes four new mathematical models for TRPTW and shows significant performance improvements compared to existing formulations, being able to optimally solve instances with up to 150 nodes within seconds.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Engineering, Industrial
Kai Zhang, Chuanhou Gao
Summary: Order picking is the retrieval process of ordered products from storage locations in warehouses. In picker-to-parts systems, multiple customer orders can be assigned to a single picker, requiring routing decisions for the picking tour. Integrated batching and routing have been found to enhance the efficiency of order picking operations compared to solving the problems separately. This study investigates the mathematical programming formulation of this integrated problem and presents improved formulations and computational results for various warehouse configurations.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Management
Jorgen Skalnes, Henrik Andersson, Guy Desaulniers, Magnus Stalhane
Summary: This paper discusses the classic Inventory Routing Problem (IRP) and proposes a branch-and-cut algorithm based on a new mathematical formulation. The algorithm improves the lower bounds by using a convex combination of extreme points, called customer schedules, to deal with time-varying demands.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Engineering, Industrial
Wouter Lefever, Faycal A. Touzout, Khaled Hadj-Hamou, El-Houssaine Aghezzaf
Summary: This paper discusses the time-constrained inventory routing problem (TCIRP) on a network with uncertain arc travel times, proposing a robust optimization approach with a controlled level of conservatism and developing a Benders' decomposition-based heuristic to cope with the resulting robust counterpart's complexity. The proposed method is compared with two standard approaches and shown to find robust solutions that are not too conservative in reasonable time.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Engineering, Industrial
Bruno E. Demantova, Cassius T. Scarpin, Leandro C. Coelho, Maryam Darvish
Summary: This paper develops a complex solution algorithm for dealing with the Inventory-Routing Problem with time windows (IRPTW). By utilizing a combination of tools, the algorithm efficiently solves the optimization problem of inventory and routing decisions. The results of the study show promising performance of the algorithm compared to a competing algorithm and provide an overview of the integration of existing techniques in the literature.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Simen T. Vadseth, Henrik Andersson, Magnus Stalhane
Summary: The paper presents a matheuristic approach to solving the inventory routing problem with the Maximum Level replenishment policy. The approach outperforms state-of-the-art methods on larger and more difficult instances, finding the best-known solution in the majority of cases.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Management
Faycal A. Touzout, Anne-Laure Ladier, Khaled Hadj-Hamou
Summary: This paper investigates a variant of the Inventory Routing Problem called the Time-Dependent IRP. By considering time-dependent travelling time functions, the optimization results are cost-efficient but computationally challenging. A proposed solution based on the observation of the structure of optimal solutions proves to be efficient in numerical experiments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Weitiao Wu, Wei Zhou, Yue Lin, Yuanqi Xie, Wenzhou Jin
Summary: The study introduces a multi-period location-inventory-routing problem and proposes a mixed integer nonlinear programming model with a two-stage hybrid metaheuristic algorithm. Experimental results show significant contributions of inventory management to total cost savings, with optimized inventory levels showing more shortages for retailers and potential increases or decreases for distribution centers.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Multidisciplinary Sciences
Phatthamon Kongkhambut, Jim Skulte, Ludwig Mathey, Jayson G. Cosme, Andreas Hemmerich, Hans Kessler
Summary: In this study, we observed a limit cycle phase in a continuously pumped atom-cavity system, characterized by emergent oscillations in the photon number. This dynamical state spontaneously breaks continuous time translation symmetry and is robust against temporal perturbations, demonstrating the realization of a continuous time crystal.
Article
Management
Claudia Archetti, Gianfranco Guastaroba, Diana L. Huerta-Munoz, M. Grazia Speranza
Summary: This paper studies an inventory routing problem and presents a matheuristic approach that uses information gathered by tabu search to build small-sized mixed-integer linear programming problems. Experimental results show that this approach outperforms other state-of-the-art algorithms in terms of solution quality.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Gizem Ozbaygin Tinic, Esra Koca, Hande Yaman
Summary: The inventory routing problem (IRP) is an integrated inventory and transportation planning problem. We have studied IRP with time windows and developed an exact algorithm to solve it, which shows strong effectiveness in identifying optimal or fairly good solutions for medium and large problem instances.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Management
Melih Celik, Claudia Archetti, Haldun Sural
Summary: This study focuses on the efficient management of storage replenishment operations in warehouses to ensure the availability of items for picking and reduce operating costs. By defining the storage replenishment routing problem and using a heuristic approach, the effects of different factors on replenishment performance were analyzed and compared to benchmarks in practice.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Operations Research & Management Science
Marcio Costa Santos, Agostinho Agra, Michael Poss
ANNALS OF OPERATIONS RESEARCH
(2020)
Article
Computer Science, Artificial Intelligence
Luis Flores-Luyo, Agostinho Agra, Rosa Figueiredo, Eladio Ocana
JOURNAL OF HEURISTICS
(2020)
Article
Computer Science, Hardware & Architecture
Fabio Barbosa, Amaro de Sousa, Agostinho Agra
Article
Management
Oeykue Naz Attila, Agostinho Agra, Kerem Akartunah, Ashwin Arulselvan
Summary: This paper investigates a lot-sizing problem with parameter uncertainties on demands and returns, focusing on remanufacturing. A min-max decomposition approach and two novel extended reformulations are proposed, showing superior performance in comparison with the standard formulation. The impact of problem parameters on computational performance is also discussed.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Filipe Rodrigues, Agostinho Agra, Lars Magnus Hvattum, Cristina Requejo
Summary: Weighted proximity search is introduced as a new method for solving complex optimization problems, where different weights are assigned to variables based on their potential to improve the solution. This approach outperforms classic proximity search and commercial solvers in a majority of cases, demonstrating the effectiveness of weighted proximity search in improving solutions.
JOURNAL OF HEURISTICS
(2021)
Article
Management
Filipe Rodrigues, Agostinho Agra
Summary: The study focuses on an integrated berth allocation and quay crane assignment and scheduling problem under uncertainty of vessel arrival times. A robust two-stage mixed integer program model and decomposition algorithm are proposed, with efficiency and effectiveness demonstrated through computational experiments on various instances.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Management
Agostinho Agra, Marielle Christiansen, Laurence Wolsey
Summary: This study addresses an inventory routing problem where a single vehicle transports goods from supply locations to demand locations. Two models are proposed and compared through computational tests using maritime transportation instances.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Fabio Barbosa, Agostinho Agra, Amaro de Sousa
Summary: The paper focuses on upgrading networks to enhance robustness to multiple failures, utilizing a mixed integer linear programming model to minimize cost and maximize network robustness. A general iterative framework is proposed to compute Pareto solutions effectively on various network topologies.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Review
Management
Filipe Rodrigues, Agostinho Agra
Summary: Port terminals play a critical role in connecting sea and land transportation, and berth allocation is among the most important planning operations. This paper provides a comprehensive survey of research on berth allocation and quay crane assignment/scheduling problems under uncertainty. Different methodologies and approaches are summarized, along with identified research trends and future directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Information Systems
Fabio Barbosa, Amaro de Sousa, Agostinho Agra, Krzysztof Walkowiak, Roza Goscien
Summary: In this study, we address the issue of multiple node failure events in dynamic Elastic Optical Networks (EONs) by proposing RMSA algorithms that combine the path disaster availability metric with spectrum usage metrics. This combination allows for a dynamic adjustment of resource utilization goals based on network load levels, aiming to achieve a good balance between spectrum usage efficiency and resilience to multiple node failures. Simulation results show that these algorithms offer the best trade-off in terms of spectrum efficiency and network resilience.
OPTICAL SWITCHING AND NETWORKING
(2021)
Article
Computer Science, Artificial Intelligence
Filipe Rodrigues, Agostinho Agra, Lars Magnus Hvattum, Cristina Requejo
Summary: This paper proposes a new weighted iterated local branching heuristic for complex optimization problems involving binary decision variables. The method improves the search algorithm efficiency by considering groups of binary variables with associated weights, which limit the number of variables that can change in each group.
JOURNAL OF HEURISTICS
(2022)
Article
Economics
Agostinho Agra, Filipe Rodrigues
Summary: This study addresses the berth allocation problem under uncertain handling times, presenting a distributionally robust two-stage model to minimize the worst-case of the expected sum of delays. Solutions are obtained through an exact decomposition algorithm, with adaptations for cases where complete recourse assumptions fail.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Operations Research & Management Science
Agostinho Agra
Summary: This paper addresses a lot-sizing problem with uncertain demands and proposes a novel approach to evaluate inventory costs. Interval uncertainty is assumed for the demands. The adversary can choose to set the demand to its higher or lower value between two consecutive production periods in order to maximize inventory costs. A mixed-integer model is created and a column-and-row generation algorithm is proposed. Computational tests are conducted to evaluate the model, decomposition algorithm, and compare the structure of solutions from the robust model to the deterministic model.
OPTIMIZATION LETTERS
(2023)
Article
Management
Filipe Rodrigues, Agostinho Agra
Summary: This paper investigates the problem of uncertain processing times in the unidirectional QCSP and proposes a distributionally robust optimization model and an exact decomposition algorithm to solve it. Extensive numerical experiments are conducted to compare the solutions obtained using stochastic programming, robust optimization, and DRO. A new method is proposed to help practitioners determine a representative set of different DRO solutions.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Filipe Rodrigues, Agostinho Agra, Cristina Requejo, Erick Delage
Summary: The paper discusses a class of min-max robust optimization problems and introduces the dual Lagrangian approach to tackle the lot-sizing problem, particularly for uncertain demands. The interpretation of Lagrangian multipliers as penalties is utilized to develop heuristic strategies for solving more complex problems efficiently, balancing robust solutions' quality and computation time.
INFORMS JOURNAL ON COMPUTING
(2021)
