Journal Description
Logistics
Logistics
is an international, scientific, peer-reviewed, open access journal of logistics and supply chain management published quarterly online by MDPI. The first issue has been released in December 2017.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), RePEc, and other databases.
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 29.7 days after submission; acceptance to publication is undertaken in 8.7 days (median values for papers published in this journal in the first half of 2024).
- Journal Rank: JCR - Q2 (Operations Research and Management Science) / CiteScore - Q1 (Management Information Systems)
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.6 (2023);
5-Year Impact Factor:
3.7 (2023)
Latest Articles
Current Advancements in Drone Technology for Medical Sample Transportation
Logistics 2024, 8(4), 104; https://doi.org/10.3390/logistics8040104 (registering DOI) - 12 Oct 2024
Abstract
Background: The integration of drone technology into healthcare logistics presents a significant opportunity to enhance the speed, reliability, and efficiency of medical sample transportation. Methods: This paper provides a narrative review of current advancements in drone technology, focusing on its application in the
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Background: The integration of drone technology into healthcare logistics presents a significant opportunity to enhance the speed, reliability, and efficiency of medical sample transportation. Methods: This paper provides a narrative review of current advancements in drone technology, focusing on its application in the rapid and secure delivery of medical samples, particularly in urban and remote regions where traditional transportation methods often face challenges. Drawing from recent studies and case reports, the review highlights the role of technologies such as artificial intelligence (AI)-driven navigation systems, real-time monitoring, and secure payload management in mitigating logistical barriers like traffic congestion and geographical isolation. Results: Based on findings from various case studies, the review demonstrates how drones can significantly reduce transportation time and costs, while improving accessibility to healthcare services in underserved areas. Conclusions: This paper concludes that, while challenges such as regulatory hurdles and privacy concerns remain, ongoing technological advancements and the development of supportive regulatory frameworks have the potential to revolutionize medical logistics, ultimately improving patient outcomes and healthcare delivery.
Full article
(This article belongs to the Section Humanitarian and Healthcare Logistics)
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Open AccessArticle
Sustainable Supplier Selection Criteria for HVAC Manufacturing Firms: A Multi-Dimensional Perspective Using the Delphi–Fuzzy AHP Method
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Amit Kumar Gupta and Imlak Shaikh
Logistics 2024, 8(4), 103; https://doi.org/10.3390/logistics8040103 - 11 Oct 2024
Abstract
Background: The supplier selection process (SSP) has grown as a crucial mechanism in organizations’ supply chain management (SCM) strategies and as a foundation for continuously gaining a competitive advantage. The concept of the circular economy has garnered significant interest due to its
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Background: The supplier selection process (SSP) has grown as a crucial mechanism in organizations’ supply chain management (SCM) strategies and as a foundation for continuously gaining a competitive advantage. The concept of the circular economy has garnered significant interest due to its ability to address both environmental and social criteria. It is highly important to carefully choose suppliers across all industries that take into account circular and sustainability issues, as well as traditional criteria. There is very limited research involving the supplier selection process in the Indian HVAC manufacturing sector. Design/Methodology/Approach: Thus, this study aimed to determine the critical factors for sustainable supplier selection for HVAC manufacturing firms using a mixed research method with three stages: a secondary study, the Delphi method, and the fuzzy analytical hierarchy process (FAHP). Thirty-two critical sub-factors were identified and grouped into eight major factors: delivery, economic, environmental, social, management and organization, quality, services, and supplier relationship. Results/Conclusions: For HVAC manufacturing firms, the major factors of delivery, quality, and economics were found to be top-ranked among the factors, followed by environmental factors. Studies in developing countries using sustainable factors are still nascent, especially in India. Originality/Value: This study’s novelty lies with the proposed eight major factors, comprising all facets of organizations, including sustainability factors. Supplier selection in HVAC manufacturing firms is exhaustively dealt with in this study, filling a gap in the existing literature. This is important because HVAC products are high-energy-consuming, high-energy-releasing, and costly.
Full article
(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics)
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Open AccessArticle
Advanced Supply Chain Management Using Adaptive Serial Cascaded Autoencoder with LSTM and Multi-Layered Perceptron Framework
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Aniruddha Deka, Parag Jyoti Das and Manob Jyoti Saikia
Logistics 2024, 8(4), 102; https://doi.org/10.3390/logistics8040102 - 10 Oct 2024
Abstract
Supply chain management is essential for businesses to handle uncertainties, maintain efficiency, and stay competitive. Financial risks can arise from various internal and external sources, impacting different supply chain stages. Companies that effectively manage these risks gain a deeper understanding of their procurement
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Supply chain management is essential for businesses to handle uncertainties, maintain efficiency, and stay competitive. Financial risks can arise from various internal and external sources, impacting different supply chain stages. Companies that effectively manage these risks gain a deeper understanding of their procurement activities and implement strategies to mitigate financial threats. This paper explores financial risk assessment in supply chain management using advanced deep learning techniques on big data. The Adaptive Serial Cascaded Autoencoder (ASCA), combined with Long Short-Term Memory (LSTM) and Multi-Layered Perceptron (MLP), is used to evaluate financial risks. A data transformation process is used to clean and prepare financial data for analysis. Additionally, Sandpiper Galactic Swarm Optimization (SGSO) is employed to optimize the deep learning model’s performance. The SGSO-ASCALSMLP-based financial risk prediction model demonstrated superior accuracy compared to traditional methods. It outperformed GRU (gated recurrent unit)-ASCALSMLP by 3.03%, MLP-ASCALSMLP by 7.22%, AE-LSTM-ASCALSMLP by 10.7%, and AE-LSTM-MLP-ASCALSMLP by 10.9% based on F1-score performance. The SGSO-ASCALSMLP model is highly efficient in predicting financial risks, outperforming conventional prediction techniques and heuristic algorithms, making it a promising approach for enhancing financial risk management in supply chain networks.
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Open AccessArticle
Exploring More Sustainable Offshore Logistics Scenarios Using Shared Resources: A Multi-Stakeholder Perspective
by
Idriss El-Thalji
Logistics 2024, 8(4), 101; https://doi.org/10.3390/logistics8040101 - 10 Oct 2024
Abstract
Offshore logistics has a substantial economic impact in the regions where offshore activities are prevalent, and has a huge opportunity to utilize the shared and collaborative logistics approach. The collaborative and shared logistics approach usually has economic, social, and environmental impacts on several
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Offshore logistics has a substantial economic impact in the regions where offshore activities are prevalent, and has a huge opportunity to utilize the shared and collaborative logistics approach. The collaborative and shared logistics approach usually has economic, social, and environmental impacts on several stakeholders within the entire business model. Therefore, the purpose of this paper is to explore and compare the benefits and implications of both separate and shared logistics approaches, from multi-stakeholder perspectives. A case asset is purposefully selected where two offshore installations are located near each other, and have the potential to collaborate and share logistics resources. Three scenarios are studied using a simulation modelling approach: (1) separate logistics vessels, (2) on-demand shared logistics vessels, and (3) scheduled shared logistics vessels. The simulated results show that the shared logistics concept, in this specific case, led to an enhancement in the delivery frequency, number of deliveries, and CO2 emissions. In addition, it provides options either to enhance vessel utilization or create revenue-generating time intervals. The scheduled shared logistics scenario is more sustainable and has a higher probability of being accepted by stakeholders, as it is driven by a revenue-generating mindset.
Full article
(This article belongs to the Special Issue Optimizations and Operations Management of Modern Logistic Systems and Supply Chains)
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A Multi-Stakeholder Information System for Traffic Restriction Management
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Maria Inês Malafaia, Joel Ribeiro and Tânia Fontes
Logistics 2024, 8(4), 100; https://doi.org/10.3390/logistics8040100 - 10 Oct 2024
Abstract
Background: In many urban areas, 80% to 90% of pollutant emissions are generated by road traffic, particularly from heavy vehicles. With the anticipated surge in e-commerce logistics, the need for effective urban mobility control measures has become urgent, focusing on traffic restrictions
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Background: In many urban areas, 80% to 90% of pollutant emissions are generated by road traffic, particularly from heavy vehicles. With the anticipated surge in e-commerce logistics, the need for effective urban mobility control measures has become urgent, focusing on traffic restrictions and efficient enforcement tools. This work introduces Log-ON, a multi-stakeholder information system designed to facilitate the implementation and management of sustainable traffic restrictions. Methods: The proposed system was developed through extensive literature reviews, expert consultations, and feedback from logistics fleet managers. User-centered mock-ups were created for various stakeholders, including the public, regulatory authorities, logistics operators, and enforcement agencies, ensuring that the system effectively addresses a diverse set of needs. Results: By taking into account a wide range of influencing factors, Log-ON functions as a decision-support tool designed to optimize access restrictions for vehicles, particularly heavy vehicles, in urban environments. Conclusions: Log-ON’s adoption promises significant improvements in urban mobility by reducing traffic-related pollution and fostering healthier, cleaner cities. However, traffic restrictions could increase delivery costs, potentially disrupting logistics operations. To address this, the development of new business models for last-mile delivery is essential, ensuring that sustainable traffic management strategies align with the economic challenges faced by logistics providers.
Full article
(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics)
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Integrating Logistics into Global Production: A New Approach
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Pablo Coto-Millán, David Paz Saavedra, Marta de la Fuente and Xose Luis Fernandez
Logistics 2024, 8(4), 99; https://doi.org/10.3390/logistics8040099 - 10 Oct 2024
Abstract
Background: Logistics has become a key driver of global economic production. This study investigates the role of logistics in global economic production by presenting a novel theoretical framework that integrates logistics performance into traditional models as a determinant production factor. Methods: Using panel
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Background: Logistics has become a key driver of global economic production. This study investigates the role of logistics in global economic production by presenting a novel theoretical framework that integrates logistics performance into traditional models as a determinant production factor. Methods: Using panel data from 85 countries between 2007 and 2022, the research measures logistics performance through the Logistics Performance Index ( ). Results: The analysis reveals that logistics performance, specifically factors such as customs efficiency, infrastructure quality, and tracking and tracing of shipments, significantly enhances global economic output. On the other hand, negative elasticities were observed for shipment timeliness and the cost competitiveness of international shipments, suggesting that inefficiencies in these areas can hinder economic growth. Conclusions: The findings underscore the need for targeted public policies to improve logistics infrastructure and efficiency, particularly in customs and trade logistics, to increase global production. Additionally, the study highlights the potential for improving the logistics sector to support sustainable development and economic interdependence among countries. This research provides important insights for policymakers and managers, indicating that effective logistics management can drive substantial improvements in production efficiency and overall economic performance.
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Open AccessArticle
Quality, Safety, and Security Systems in the Greek Port Industry: Over Twenty Years of Research, Empirical Evidence, and Future Perspectives
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Constantinos Chlomoudis, Petros Kostagiolas, Petros Pallis and Charalampos Platias
Logistics 2024, 8(4), 98; https://doi.org/10.3390/logistics8040098 - 9 Oct 2024
Abstract
Background: Quality, Safety and Security are embedded in all aspects of port operations and are crucial for port industry stakeholders. Over the past decades, numerous assurance systems, codes, and regulations for quality, safety, and security have been developed and implemented in ports
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Background: Quality, Safety and Security are embedded in all aspects of port operations and are crucial for port industry stakeholders. Over the past decades, numerous assurance systems, codes, and regulations for quality, safety, and security have been developed and implemented in ports world-wide. This paper examines key insights for the implementation those systems in ports, reviewing over 20 years of empirical research on the impact and outcomes of such systems in Greek ports and internationally. Methods: It compares and discusses evidence from two empirical surveys spanning the first two decades of the 21rst century. The first survey was conducted in 2011 (with evidence from 2000 to 2011) including 12 major Greek ports (SAs) and the second one was conducted up to 2022–2023, including 23 over 25 Greek ports (the same SAs and other ones from the Greek TEN-T network). Results: The higher-level scope of this paper is to investigate critical perspectives on and trends in quality, safety, and security systems in the port industry. Conclusions: This investigation aims to strengthen the assumption that quality, safety, and security play a pivotal role in shaping the image, performance, and growth of ports.
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(This article belongs to the Section Maritime and Transport Logistics)
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Open AccessArticle
Assessment of the Position of North Adriatic Terminals in Container Market Based on Different Indices
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Svjetlana Hess, Mirano Hess, Marko Novaselić and Luka Grbić
Logistics 2024, 8(4), 97; https://doi.org/10.3390/logistics8040097 - 7 Oct 2024
Abstract
Background: This paper addresses the common question of how service providers compare to their competitors and what their competitive advantages are. It focuses on the North Adriatic ports of Trieste, Koper, Rijeka, Venice, and Ravenna, all members of the North Adriatic Ports
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Background: This paper addresses the common question of how service providers compare to their competitors and what their competitive advantages are. It focuses on the North Adriatic ports of Trieste, Koper, Rijeka, Venice, and Ravenna, all members of the North Adriatic Ports Association, analyzing their position, size, competitiveness, and role in the container market. Methods: The research employs three distinct methods: market structure analysis using several concentration indices, the R method for ranking terminals, and aggregation of these indices to create a combined index for port performance. Results: Based on the rankings, indicators, the BCG matrix, and future development plans for each terminal, the ports are ranked as follows: Koper, Rijeka, Trieste, Venice, and Ravenna. Koper emerges as the leader, positioned in the high market share and strong growth category. This advantageous position allows Koper to efficiently attract traffic without requiring substantial investments. Conclusions: The contribution of the work is that the specific measure indices were applied, which were not used in the analysis of the North Adriatic container terminals until now. The research provides both a broad and detailed understanding of the position, role, and condition of each terminal. This insight enables stakeholders to take timely, strategic actions aimed at boosting productivity and traffic, ultimately improving their competitive standing.
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(This article belongs to the Section Maritime and Transport Logistics)
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Optimizing a Dynamic Vehicle Routing Problem with Deep Reinforcement Learning: Analyzing State-Space Components
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Anna Konovalenko and Lars Magnus Hvattum
Logistics 2024, 8(4), 96; https://doi.org/10.3390/logistics8040096 - 2 Oct 2024
Abstract
Background: The dynamic vehicle routing problem (DVRP) is a complex optimization problem that is crucial for applications such as last-mile delivery. Our goal is to develop an application that can make real-time decisions to maximize total performance while adapting to the dynamic nature
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Background: The dynamic vehicle routing problem (DVRP) is a complex optimization problem that is crucial for applications such as last-mile delivery. Our goal is to develop an application that can make real-time decisions to maximize total performance while adapting to the dynamic nature of incoming orders. We formulate the DVRP as a vehicle routing problem where new customer requests arrive dynamically, requiring immediate acceptance or rejection decisions. Methods: This study leverages reinforcement learning (RL), a machine learning paradigm that operates via feedback-driven decisions, to tackle the DVRP. We present a detailed RL formulation and systematically investigate the impacts of various state-space components on algorithm performance. Our approach involves incrementally modifying the state space, including analyzing the impacts of individual components, applying data transformation methods, and incorporating derived features. Results: Our findings demonstrate that a carefully designed state space in the formulation of the DVRP significantly improves RL performance. Notably, incorporating derived features and selectively applying feature transformation enhanced the model’s decision-making capabilities. The combination of all enhancements led to a statistically significant improvement in the results compared with the basic state formulation. Conclusions: This research provides insights into RL modeling for DVRPs, highlighting the importance of state-space design. The proposed approach offers a flexible framework that is applicable to various variants of the DVRP, with potential for validation using real-world data.
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(This article belongs to the Section Artificial Intelligence, Logistics Analytics, and Automation)
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Framework for the Sustainable Modeling of Electric Truck Fleet Usage
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Irina Yatskiv (Jackiva), Jurijs Tolujevs and Vladimirs Petrovs
Logistics 2024, 8(4), 95; https://doi.org/10.3390/logistics8040095 - 26 Sep 2024
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Background: As road transport companies increasingly integrate electric trucks (eTrucks) into urban fleets, evaluating their performance in real-world conditions is essential for effective fleet management and infrastructure planning. Methods: This study introduces TraPodSim, a simulation system designed to assess the key performance indicators
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Background: As road transport companies increasingly integrate electric trucks (eTrucks) into urban fleets, evaluating their performance in real-world conditions is essential for effective fleet management and infrastructure planning. Methods: This study introduces TraPodSim, a simulation system designed to assess the key performance indicators (KPIs) of eTrucks and other vehicle types. Using real geographic data, transportation routes, and technical vehicle specifications, the system simulates daily operations under user-defined conditions. Results: TraPodSim produces 20 physical indicators, providing detailed insights into the daily performance of each vehicle in the fleet. These indicators help evaluate fleet efficiency, energy consumption, and overall operational effectiveness. Conclusions: TraPodSim offers transport companies a valuable tool for optimizing fleet configurations and analyzing the use of private or public battery-charging stations, enabling the efficient integration of eTrucks into existing transportation networks.
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Open AccessReview
Conceptualization of Supplier Involvement in Product Development Based on a Systematic Review of 47 Definitions
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Filip Flankegård, Glenn Johansson, Anna Granlund and Peter E. Johansson
Logistics 2024, 8(4), 94; https://doi.org/10.3390/logistics8040094 - 25 Sep 2024
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Background: Supplier involvement in product development has proven beneficial for companies and is a phenomenon researched in various domains. The definitions of supplier involvement represent points of origin and dimensions addressed in research. Still, there is no overview of these definitions and
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Background: Supplier involvement in product development has proven beneficial for companies and is a phenomenon researched in various domains. The definitions of supplier involvement represent points of origin and dimensions addressed in research. Still, there is no overview of these definitions and dimensions. This study reviews current definitions of the phenomenon of supplier involvement in product development and develops a conceptual model outlining its main dimensions. Methods: A systematic literature review is conducted to provide an overview of explicit definitions of supplier involvement in product development. By identifying the elements of these definitions, a conceptual model is developed to demonstrate how the phenomenon has been conceptualized in literature. Results: The results include an overview of 47 explicit definitions of supplier involvement in product development, a conceptual model including the identified dimensions, research gaps, and questions for future research. Conclusions: Supplier involvement in product development is a complex phenomenon with interdependencies between its key dimensions. A conceptual model of supplier involvement is presented, which is useful for categorizing research to identify research gaps and avenues for future research.
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On-Demand Warehousing Platforms: Evolution and Trend Analysis of an Industrial Sharing Economy Model
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Valerio Elia, Maria Grazia Gnoni and Fabiana Tornese
Logistics 2024, 8(4), 93; https://doi.org/10.3390/logistics8040093 - 24 Sep 2024
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Background: The on-demand warehousing (ODW) model is emerging as a platform-enabled logistics solution based on resource sharing for businesses needing storage space. It is based on a business-to-business marketplace where companies can provide (or request) storage services with an elevated level of
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Background: The on-demand warehousing (ODW) model is emerging as a platform-enabled logistics solution based on resource sharing for businesses needing storage space. It is based on a business-to-business marketplace where companies can provide (or request) storage services with an elevated level of flexibility. The literature focusing on this topic is still scarce, and while the potential advantages of such a model seem quite clear, challenges and criticalities need to be further explored. Methods: Starting from a state-of-the-art analysis of ODW, a two-step methodology was adopted: first, a SWOT analysis was conducted to help summarize the challenges related to this emerging model. Then, an exploratory analysis of multiple case studies was employed to provide a first discussion on the advantages and criticalities of this model, highlighting its latest evolution. Results: The ODW model is still evolving, as several former pure ODW platforms have been changing their business model to become on-demand 4PLs (defined as “mixed ODW-4PLs”), adapting their core activities to manage the criticalities of on-demand services. Conclusions: This study represents the first attempt to investigate benefits and criticalities of ODW models, outlining the latest trend of ODW and identifying two distinct types of ODW model currently present on the market.
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Comparative Analysis of Train Departure Strategies in a Container Shipment
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Alessia Giulianetti, Marco Gotelli and Anna Sciomachen
Logistics 2024, 8(3), 92; https://doi.org/10.3390/logistics8030092 - 18 Sep 2024
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Background: We focus on the inland rail forwarding of import containers from a marine terminal. Specifically, we present a discrete-event simulation study related to container-loading operations by train, evaluating different train departure policies within a predetermined schedule based on the capacity of
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Background: We focus on the inland rail forwarding of import containers from a marine terminal. Specifically, we present a discrete-event simulation study related to container-loading operations by train, evaluating different train departure policies within a predetermined schedule based on the capacity of the rail network. The aim is threefold: manage more containers shipped by train, improve terminal operational efficiency, and increase the rail share. Methods: The proposed procedures take full advantage of the digitization and visualization of data currently present in the terminal with the aim of improving the performance indices of interest, thereby increasing the terminal‘s operational efficiency. We evaluate the medium- and long-term impact of alternative strategies on container dwell times and the possible increase in the number of containers shipped by train. Results: The computational tests are performed with data from a terminal in the port of Genoa (Italy). The results show the relationships between train departure management policies and train departure distributions. The number of departing trains, cancelled trains, and trains departing with load percentages below 70% is studied. Average loads per train and estimated delays are also analyzed. Conclusions: It is noted that the results, which can be obtained with data from any terminal, are of great importance for optimizing operational management, offering practical solutions to improve efficiency and reduce container downtime.
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Open AccessArticle
Advanced Queueing and Location-Allocation Strategies for Sustainable Food Supply Chain
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Amirmohammad Paksaz, Hanieh Zareian Beinabadi, Babak Moradi, Mobina Mousapour Mamoudan and Amir Aghsami
Logistics 2024, 8(3), 91; https://doi.org/10.3390/logistics8030091 - 14 Sep 2024
Abstract
Background: This study presents an integrated multi-product, multi-period queuing location-allocation model for a sustainable, three-level food supply chain involving farmlands, facilities, and markets. The model employs M/M/C/K queuing systems to optimize the transportation of goods, enhancing efficiency and sustainability. A mixed-integer nonlinear programming
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Background: This study presents an integrated multi-product, multi-period queuing location-allocation model for a sustainable, three-level food supply chain involving farmlands, facilities, and markets. The model employs M/M/C/K queuing systems to optimize the transportation of goods, enhancing efficiency and sustainability. A mixed-integer nonlinear programming (MINLP) approach is used to identify optimal facility locations while maximizing profitability, minimizing driver waiting times, and reducing environmental impact. Methods: The grasshopper optimization algorithm (GOA), a meta-heuristic algorithm inspired by the behavior of grasshopper swarms, is utilized to solve the model on a large scale. Numerical experiments demonstrate the effectiveness of the proposed model, particularly in solving large-scale problems where traditional methods like GAMS fall short. Results: The results indicate that the proposed model, utilizing the grasshopper optimization algorithm (GOA), effectively addresses complex and large-scale food supply chain problems. Compared to GAMS, GOA achieved similar outcomes with minimal differences in key metrics such as profitability (with a gap ranging from 0.097% to 1.11%), environmental impact (0.172% to 1.83%), and waiting time (less than 0.027%). In large-scale scenarios, GOA significantly reduced processing times, ranging from 20.45 to 64.78 s. The optimization of processing facility locations within the supply chain, based on this model, led to improved balance between cost (up to $74.2 million), environmental impact (122,112 hazardous units), and waiting time (down to 11.75 h). Sensitivity analysis further demonstrated that increases in truck arrival rates and product value had a significant impact on improving supply chain performance.
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(This article belongs to the Section Sustainable Supply Chains and Logistics)
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Gresilient Supplier Evaluation and Selection under Uncertainty Using a Novel Streamlined Full Consistency Method
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Mohammad Hashemi-Tabatabaei, Maghsoud Amiri and Mehdi Keshavarz-Ghorabaee
Logistics 2024, 8(3), 90; https://doi.org/10.3390/logistics8030090 - 12 Sep 2024
Abstract
Background: Supply chain management (SCM) plays a fundamental role in the progress and success of organizations and has continuously evolved to better adapt to today’s complex business environments. Consequently, the issue of supplier evaluation and selection (SES), which is one of the
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Background: Supply chain management (SCM) plays a fundamental role in the progress and success of organizations and has continuously evolved to better adapt to today’s complex business environments. Consequently, the issue of supplier evaluation and selection (SES), which is one of the most critical decisions in SCM, has gained special significance and has been examined from various perspectives. The concept of green and resilient (gresilient) SCM has emerged in response to recent concerns about environmentally friendly production and operations, as well as organizations’ ability to cope with crises and disasters. In the rapidly growing construction industry, applying gresilient principles can ensure green operations and help overcome future challenges. Methods: This study focuses on gresilient SES in a real-world construction case study, proposing a streamlined FUCOM (S-FUCOM) approach. The proposed method streamlines traditional FUCOM processes to solve decision-making problems in deterministic and uncertain environments. Several numerical examples are provided to illustrate its applicability. Results: the case study results identify air emissions, environmental management systems, and restorative capacity as the most critical gresilient SES criteria. Conclusions: The third supplier emerged as the top performer based on decision-making indicators. Finally, a sensitivity analysis was conducted across 20 scenarios, demonstrating that S-FUCOM is robust and provides stable results.
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(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics)
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Open AccessArticle
Efficiency of Inventory in Thai Hospitals: Comparing Traditional and Vendor-Managed Inventory Systems
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Sarunya Adirektawon, Anuchai Theeraroungchaisri and Rungpetch C. Sakulbumrungsil
Logistics 2024, 8(3), 89; https://doi.org/10.3390/logistics8030089 - 10 Sep 2024
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Background: Traditional procurement and price negotiation methods in public hospitals in Thailand involve group purchasing agreements and bulk orders, posing challenges to improving inventory management efficiency. The vendor-managed inventory (VMI) model is a promising alternative for enhancing hospital performance, especially during crises.
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Background: Traditional procurement and price negotiation methods in public hospitals in Thailand involve group purchasing agreements and bulk orders, posing challenges to improving inventory management efficiency. The vendor-managed inventory (VMI) model is a promising alternative for enhancing hospital performance, especially during crises. This study aimed to assess the potential cost savings in implementing VMI in a large general hospital in Thailand. Methods: A simulation modeling approach was used to compare the current inventory system with three VMI models: VMI1, focused on improving inventory turnover rate (ITR); VMI2, emphasized frequent replenishment with a 1-month supply; and VMI3, eliminated safety stock. Results: The results demonstrated significant cost savings, with potential reductions in total inventory management expenses. Specifically, VMI1 improved ITR from 6.31 to 7.76, reducing average inventory by 36% and cutting management costs by 40%. VMI2, with an ITR of 12.80, reduced inventory by 44% and saved 47% in management costs, while VMI3 achieved a 70% reduction in inventory and a 69% saving in management costs. Conclusions: This study highlights the VMI’s transformative potential in hospital inventory management, demonstrating significant cost savings. However, in the public sector, the feasibility of procurement regulations requires further exploration.
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Open AccessArticle
Factory Logistics Improvement: A Case Study Analysis of Companies in Northern Thailand, 2022–2024
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Sakgasem Ramingwong, Apichat Sopadang, Korrakot Yaibuathet Tippayawong and Jutamat Jintana
Logistics 2024, 8(3), 88; https://doi.org/10.3390/logistics8030088 - 9 Sep 2024
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Background: Thailand’s logistics costs significantly exceed global averages. This study examines the novel application of a triple-helix model in factory logistics improvement projects in Northern Thailand from 2022 to 2024, addressing industrial logistics inefficiencies. Methods: The project involved 30 factories across various sectors,
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Background: Thailand’s logistics costs significantly exceed global averages. This study examines the novel application of a triple-helix model in factory logistics improvement projects in Northern Thailand from 2022 to 2024, addressing industrial logistics inefficiencies. Methods: The project involved 30 factories across various sectors, employing a case study methodology to analyze improvement initiatives in transportation, warehouse/inventory management, and logistics administration. Results: Transportation management interventions yielded up to 25% cost savings and improved delivery performance. Warehouse and inventory management upgrades led to inventory cost reductions of up to 55%. Logistics administrative improvements resulted in up to 20% cost savings and enhanced planning capabilities. Conclusions: The project demonstrates the effectiveness of the triple-helix model in facilitating knowledge transfer and practical improvements in industrial logistics. These findings are valuable for Thai industries, policymakers, and logistics managers globally, offering a blueprint for similar initiatives in developing economies. The success of this approach provides practical insights for optimizing logistics operations, potentially benefiting supply chain stakeholders, economic planners, and researchers seeking to enhance logistics efficiency and reduce costs in various industrial contexts.
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Open AccessArticle
Ranking and Challenges of Supply Chain Companies Using MCDM Methodology
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Alaa Fouad Momena, Kamal Hossain Gazi, Mostafijur Rahaman, Anna Sobczak, Soheil Salahshour, Sankar Prasad Mondal and Arijit Ghosh
Logistics 2024, 8(3), 87; https://doi.org/10.3390/logistics8030087 - 5 Sep 2024
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Background: Supply chain companies have merits and demerits regarding operational and economic transactional policies. The effectiveness of supply chain companies corresponds to a cumulative score on a multi-criteria and perspectives-based evaluation. In this paper, we analyse the performances and challenges of several
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Background: Supply chain companies have merits and demerits regarding operational and economic transactional policies. The effectiveness of supply chain companies corresponds to a cumulative score on a multi-criteria and perspectives-based evaluation. In this paper, we analyse the performances and challenges of several celebrated e-commerce companies to perceive their overall impression of supply chain management. Method: A mathematical model is framed as a multi-criteria decision-making (MCDM) problem with challenges as criteria and companies as alternatives. The criteria importance through inter-criteria correlation (CRITIC) method is used in this paper to adjust weights representing the available data. The ranking of e-commerce companies is evaluated using multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) method. Results: This model investigates the most dependent criteria and sub-criteria for the adaptation challenges of supply chain companies (SCCs). Furthermore, the SCCs are prioritized based on various conflicting criteria. Conclusion: Various challenges of SCCs, like logistics constraints, disruptions in supply chains, issues with technology, ethical sourcing and inconsistency between the products’ availability and the pace of consumption, are considered and analysed. We amassed the difficulties as criteria and sub-criteria in a numerical process using the MCDM approach. Additionally, the sensitivity and comparative of several optimal phenomena are analysed based on distinctive combinations of challenges in the ranking arena.
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(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics)
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Open AccessArticle
Optimization of Hub-Based Milkrun Supply
by
Tamás Bányai
Logistics 2024, 8(3), 86; https://doi.org/10.3390/logistics8030086 - 3 Sep 2024
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Background: Milkrun-based material supply plays an important role in the automotive industry, as it is a material supply concept where high efficiency can be achieved. When implementing milkrun-based material supply, the milkrun supply of the production plant often has to be integrated with
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Background: Milkrun-based material supply plays an important role in the automotive industry, as it is a material supply concept where high efficiency can be achieved. When implementing milkrun-based material supply, the milkrun supply of the production plant often has to be integrated with an existing warehouse material handling system, which frequently leads to a less efficient solution. Methods: In this paper, the author investigates the impact of a hub-based milkrun supply, where the collection processes in the component’s warehouse and the distribution processes in the assembly plant are connected to a hub, which is responsible for the sequencing of component demands. After a systematic literature review, the paper introduces a novel mathematical model, which makes it possible to describe the conventional milkrun-based solutions, the hub-based milkrun solutions, and to compare them in terms of the length of transportation routes, transportation time, total service time, and virtual emission points of view. Results: The scenario analysis demonstrates that the hub-based solution can lead to an efficiency improvement of about 13% in total service time, 23% savings in transportation time, and 45% savings in transportation time in the component’s warehouse. Conclusions: The article’s findings suggest that implementing a hub-based milkrun system in automotive material supply can significantly enhance efficiency. The described approach could lead to more streamlined operations in production plants by optimizing the integration of milkrun systems.
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Open AccessArticle
Simulation Model for a Sustainable Food Supply Chain in a Developing Country: A Case Study of the Banana Supply Chain in Malawi
by
Evance Hlekwayo Moyo, Stephen Carstens and Jackie Walters
Logistics 2024, 8(3), 85; https://doi.org/10.3390/logistics8030085 - 25 Aug 2024
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Background: Sustainability in food supply chains is desired for production, logistics, and waste management. However, food supply chains (SCs) have complex systems that differ from other SCs. Managing such complexities is challenging for small and medium-sized enterprises (SMEs) due to their heightened
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Background: Sustainability in food supply chains is desired for production, logistics, and waste management. However, food supply chains (SCs) have complex systems that differ from other SCs. Managing such complexities is challenging for small and medium-sized enterprises (SMEs) due to their heightened constraints, such as limited resources and inadequate awareness. Despite the challenges, there is fragmented research, understanding, and approaches to assist SMEs. SC designs need to be adapted so that SMEs can navigate the challenges and avert high wastage. The main objective of this research was to identify the practices influencing sustainable SC designs in a developing country and create a simulation model to illustrate the potential benefits and challenges of promoting sustainability in the banana SC in Malawi. Methods: Mixed-methods research was utilised, employing a literature review, participant interviews, observations, and survey data collected from 353 participants from three districts in Malawi to gain insight into the banana SC problem, establish objectives, and develop a simulation model complemented by design science research. Results: The research identified awareness, collaboration, efficiency, governance, knowledge sharing, and resilience as sustainability practices in the case study banana SC, thus forming a sustainability model. Simulation results showed improvements in key performance indicators like shelf-life, lead-time, quality, throughput, and waste through SC operation reorganisation. Conclusions: Sustainable models must be tailored to the specific challenges inherent in developing food supply chains in developing nations. The development of the models has significant managerial implications, notably enhancing strategic planning, operational efficiency, risk management, alignment of sustainability goals, performance monitoring, stakeholder engagement, and resource optimisation.
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