Article
Computer Science, Artificial Intelligence
Yulia Karpova, Fulgencia Villa, Eva Vallada, Miguel angel Vecina
Summary: This study addresses the problem of dynamic relocation of ambulances through the design and development of heuristic tools, aiming to improve the efficiency of prehospital care.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Marko Durasevic, Mateja Dumic
Summary: This paper investigates the application of genetic programming to automatically design effective relocation rules, which outperform manually designed rules and demonstrate good generalization performance across unseen problems, presenting a viable alternative to existing manual designs in the area of container relocation problems.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Interdisciplinary Applications
Chang Lv, Chaoyong Zhang, Yaping Ren, Leilei Meng
Summary: This paper focuses on the Dual-mode integrated Location Routing Problem (DMI-LRP) in modern supply logistics system. The authors propose a fuzzy correlation-based approach for location and allocation, and design an adaptive neighborhood search algorithm for path planning. Results from numerical experiments demonstrate the feasibility and efficiency of the proposed method, especially for large-scale problems.
COMPUTERS & OPERATIONS RESEARCH
(2022)
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
Multidisciplinary Sciences
Lijun Fan
Summary: As competition intensifies, more companies are outsourcing their package distribution operations to professional Third-Party Logistics (3PL) fleets, which have started using Electric Vehicles (EVs) for transportation. This paper addresses the Time-Dependent Open Electric Vehicle Routing Problem with Hybrid Energy Replenishment Strategies (TDOEVRP-HERS) in urban distribution. It considers the impact of dynamic urban transport networks on EV energy consumption and develops an approach to estimate energy usage. Additionally, the research proposes a mixed-integer programming model to minimize distribution costs for 3PL fleets and presents a hybrid adaptive large neighborhood search algorithm for solving the model.
Article
Economics
Tiago A. Santos, P. Martins, C. Guedes Soares
Summary: This paper presents a mathematical model for calculating the generalized costs of transporting containers and applies it in a case study on the consequences of terminal relocation in the port of Lisbon. The model shows significant implications on the delimitation of container terminal potential hinterlands across southern Portugal. Conclusions and policy recommendations are made regarding the relative competitiveness and suitability of the relocation.
JOURNAL OF TRANSPORT GEOGRAPHY
(2021)
Article
Management
Leopoldo E. Cardenas-Barron, Rafael A. Melo
Summary: This study focuses on an NP-hard selective and periodic inventory routing problem (SPIRP) in a waste vegetable oil collection environment, proposing a MIP-based heuristic approach that proves to be fast and effective in improving existing best results.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
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
Engineering, Industrial
Sohrab Faramarzi-Oghani, Parisa Dolati Neghabadi, El-Ghazali Talbi, Reza Tavakkoli-Moghaddam
Summary: This article provides a literature review on the application of meta-heuristic algorithms in sustainable supply chain management (SSCM), based on the analysis of 160 selected papers. The findings show a significant growth in research in this field in recent years, with hybrid meta-heuristics overtaking pure meta-heuristics. The genetic algorithm (GA) and the non-dominated sorting GA (NSGA-II) are the most commonly used single- and multi-objective algorithms. The study also highlights the importance of addressing sustainability aspects in product distribution and vehicle routing, as well as the growing attention to the economic-environmental category of sustainability.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Hernan Lespay, Karol Suchan
Summary: This study introduces a territory design for the multi-period vehicle routing problem with time windows (TD-MPVRPTW) in a food company's distribution center. The study proposes a heuristic algorithm to solve the problem and compares it with existing solutions. The results show that the proposed algorithm can provide high-quality solutions within a reasonable running time. The study also presents a methodology in which the computed territories from the past month are used for the operational routing in the following month. Evaluation results demonstrate that the territories obtained with this methodology can significantly improve service levels and require fewer vehicles for delivery.
COMPUTERS & OPERATIONS RESEARCH
(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
Management
Antonio Carlos Bonassa, Claudio Barbieri da Cunha, Cassiano Augusto Isler
Summary: This paper presents a study on the Dynamic Multi-Period Auto-Carrier Transportation Problem (DM-PACTP) in the automotive industry in Brazil. The goal is to find the optimal vehicle loading plan that minimizes transportation cost and meets delivery deadlines. A Multi-Start Local Search Heuristic (MSLSH) is proposed to solve large-scale instances. Experimental results demonstrate the effectiveness of the heuristic, achieving optimal solutions for medium-sized instances and significant cost reductions for large-sized instances compared to manual allocation.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Economics
Simon Belieres, Mike Hewitt, Nicolas Jozefowiez, Frederic Semet
Summary: This study investigates the operations of a 3PL service provider in the supply chain management of a French restaurant chain, using a new network reduction heuristic algorithm to solve the Logistics Service Network Design Problem. Experimental results demonstrate the efficiency of the proposed approach and its alignment with practical operational needs, while also uncovering the impact of distribution strategies on transportation planning and logistics costs.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2021)
Article
Engineering, Civil
Tianhong Zhao, Wei Tu, Zhixiang Fang, Xiaofan Wang, Zhengdong Huang, Shengwu Xiong, Meng Zheng
Summary: In response to the COVID-19 pandemic, a new delivery route optimization approach has been proposed to reduce the virus transmission risk during the delivery of essential living materials. Using a complex network-based virus transmission model, the approach significantly decreased the COVID-19 transmission risk by 67.55% compared to traditional distance-based optimization methods, showing potential for effective response to COVID-19 in transportation sector.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Industrial
Bingqian Wang, Xiuqing Yang, Mingyao Qi
Summary: This paper investigates an order picking tactic in a robotic mobile fulfillment system that allows racks to move between multiple picking stations to process more orders and save time. Numerical experiments show that inter-station operations can significantly reduce order throughput time.
FLEXIBLE SERVICES AND MANUFACTURING JOURNAL
(2023)
Article
Computer Science, Interdisciplinary Applications
Alessandro Hill, Roberto Baldacci, Stefan Voss
Summary: This work proposes concepts and solution methodologies for strategic network design problems in highly data-sensitive industries, focusing on cost-efficient tree-structured communication infrastructure. The novel side constraints related to customer privacy significantly complicate the optimization problem, and various privacy models are studied to address these constraints. Strong non-compact integer programming formulations are developed and tested on literature-based instances to analyze performance.
JOURNAL OF COMBINATORIAL OPTIMIZATION
(2022)
Review
Management
Mariam Gomez Sanchez, Eduardo Lalla-Ruiz, Alejandro Fernandez Gil, Carlos Castro, Stefan Voss
Summary: Project Management is crucial in competitive industries. The RCMPSP is about assigning start times to jobs in multiple projects with limited resources. This research analyzes different variants of the problem and proposes a taxonomy for identification and analysis. It also classifies and analyzes solution methods and benchmarks for RCMPSP, and discusses its connection to practice and future research opportunities.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Engineering, Industrial
Philip Cammin, Jingjing Yu, Stefan Voss
Summary: Despite its importance, many port authorities do not provide continuous or publicly available air emissions inventories, which obscures the emissions contribution of ports. In this paper, we propose port vessel emissions prediction models using machine learning algorithms and vessel data to enable accurate prediction and creation of emissions inventories.
FLEXIBLE SERVICES AND MANUFACTURING JOURNAL
(2023)
Article
Management
Raka Jovanovic, Antonio P. Sanfilippo, Stefan Voss
Summary: This passage introduces the Clique Partitioning Problem (CPP), which aims to maximize the sum of edge weights over disjoint subsets (cliques) of vertices. The novel fixed set search (FSS) metaheuristic, including a greedy randomized adaptive search procedure (GRASP) and a learning mechanism, is applied to solve the NP-hard problem efficiently. The proposed approach outperforms state-of-the-art metaheuristics for the CPP, generating numerous new best solutions for commonly used test instances.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Review
Management
Malek Sarhani, Stefan Voss, Raka Jovanovic
Summary: This article discusses the importance of initialization in metaheuristics and highlights the lack of comprehensive reviews in the field. It provides a new review, covering the main metaheuristic methods, diversification mechanisms, challenging optimization problems, and the initialization of local search methods.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Article
Engineering, Industrial
Yingjie Fan, Frank Schwartz, Stefan Voss, David L. L. Woodruff
Summary: Catastrophe-related insurance is an effective tool for global corporations to reduce economic losses caused by high impact events. This study explores the impact of purchasing catastrophe insurance on supply chain operational planning, finding that it may be optimal for supply chains to scrap redundant products in catastrophes.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Pasquale Legato, Rina Mary Mazza, Stefan Voss
Summary: Path finding for human-operated vehicles in a maritime container terminal can be challenging due to dynamic traffic conditions and self-governing decisions. Preventing collision and interference among internal transfer vehicles is crucial for minimizing congestion during container transfers. The proposed simulation framework combines local and global search strategies, allowing for path finding decisions based on dynamic or static data. Numerical experiments demonstrate the effectiveness of this approach, particularly in critical extraordinary events where the performance difference between strategies becomes more significant.
SIMULATION MODELLING PRACTICE AND THEORY
(2023)
Article
Green & Sustainable Science & Technology
Stefan Voss
Summary: This paper explores the application of generative AI tools in sustainable passenger transportation, focusing on issues related to disturbances in public transport, such as bus bunching and bus bridging. Generative AI tools appear to provide meaningful insights and provoke a lot of contemplation, although their academic use is still limited.
Article
Green & Sustainable Science & Technology
Dominik Bietsch, Robert Stahlbock, Stefan Voss
Summary: This paper examines the application of generative adversarial networks (GANs) in generating synthetic tabular electronic health records (EHR) data for predicting patient length of stay (LOS) in the healthcare industry. By comparing different GAN models, it is found that the Conditional Tabular GAN (CTGAN) performs better in this use case. However, there is still room for improvement when applying state-of-the-art GAN models to clinical healthcare data.
Article
Green & Sustainable Science & Technology
Carlos D. Paternina-Arboleda, Dayana Agudelo-Castaneda, Stefan Voss, Shubhendu Das
Summary: Maritime ports play a crucial role in trade and economies, but their operations have significant impacts on air quality and climate change. Predictive modeling of port emissions can help identify areas of concern, evaluate emission reduction strategies, and promote sustainable development. Advanced machine learning techniques can contribute to understanding port emissions and fostering sustainability in the maritime industry.
Article
Green & Sustainable Science & Technology
Wei Le, Adriana Moros-Daza, Maria Jubiz-Diaz, Stefan Voss
Summary: This work introduces a blockchain-based solution with a simulated prototype to enhance electronic seals for containers in port terminals. An electronic seal design and a blockchain prototype for container data flow were implemented. Performance tests were conducted to evaluate the prototype's results, and security issues in the blockchain were discussed using game theory. The simulation concluded that the blockchain improves transaction efficiency. As no prior studies have integrated blockchain technology with electronic seals, this work aims to combine them to enhance the security of transferred data due to the immutability of blockchain.
Article
Transportation
Philip Cammin, Kai Bruessau, Stefan Voss
Summary: Many maritime ports lack transparency by not publicly providing port air emissions reporting. This study develops an assessment method and applies it to the top 49 container ports worldwide, revealing that less than half of the assessed ports offer publicly available emissions reporting. The proposed classification scheme aids stakeholders in improving emissions reporting and enhancing environmental sustainability reporting.
MARITIME TRANSPORT RESEARCH
(2022)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Adriana Moros-Daza, Rene Amaya-Mier, Guisselle Garcia, Stefan Voss
Summary: In the context of port communities, Port Community Systems (PCS) are commonly used technological developments that provide services such as information exchange, electronic customs declarations, goods control and tracking, and statistics. However, there is a need to develop an updated version of PCS to meet the requirements of both developed and emerging economies and incorporate new technologies. This study proposes a new service called hinterland intermodal routing service to be included in PCS, which utilizes an optimization model to deliver a sustainable and cost-effective intermodal transport network, aiming to reduce the environmental impact and transportation costs in Colombia.
COMPUTATIONAL LOGISTICS (ICCL 2022)
(2022)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Mehrdad Amirghasemi, Marcella Bernardo Papini, Stefan Voss
Summary: This paper proposes a hybrid, modular solution strategy that embeds an adaptive improvement technique into a genetic algorithm and applies it to both the quadratic semi-assignment problem and the berth allocation problem. By embedding important parameters in the employed genomes, the strategy achieves self-adaptivity. Computational experiments demonstrate that the presented procedure can find optimal solutions in most cases and can find them very quickly for small instances.
COMPUTATIONAL LOGISTICS (ICCL 2022)
(2022)
Article
Transportation Science & Technology
Liping Ge, Stefan Voss, Lin Xie
Summary: This paper discusses disturbances in the context of public transportation and explores various methods to cope with them. The research finds that different strands of literature exist that may benefit from better connected and intertwined development.
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)
