Pub Date : 2024-08-09DOI: 10.3390/logistics8030080
Davies K. Bett, Islam Ali, M. Gheith, Amr Eltawil
Background: Container terminals (CTs) have constantly administered truck appointment systems (TASs) to effectively accomplish the planning and scheduling of drayage operations. However, since the operations in the gate and yard area of a CT are stochastic, there is a need to incorporate uncertainty during the development and execution of appointment schedules. Further, the situation is complicated by disruptions in the arrival of external trucks (ETs) during transport, which results in congestion at the port due to unbalanced arrivals. In the wake of Industry 4.0, simulation can be used to test and investigate the present CT configurations for possible improvements. Methods: This paper presents a simulation optimization (SO) and simulation-based optimization (SBO) iteration framework which adopts a dual transactions approach to minimize the gate operation costs and establish the relationship between productivity and service time while considering congestion in the yard area. It integrates the use of both the developed discrete event simulation (DES) and a mixed integer programming (MIP) model from the literature to iteratively generate an improved schedule. The key performance indicators considered include the truck turnaround time (TTT) and the average time the trucks spend at each yard block (YB). The proposed approach was verified using input parameters from the literature. Results: The findings from the SO experiments indicate that, at most, two gates were required to be opened at each time window (TW), yielding an average minimum operating cost of USD 335.31. Meanwhile, results from the SBO iteration experiment indicate an inverse relationship between productivity factor (PF) values and yard crane (YC) service time. Conclusions: Overall, the findings provided an informed understanding of the need for dynamic scheduling of available resources in the yard to cut down on the gate operating costs. Further, the presented two methodologies can be incorporated with Industry 4.0 technologies to design digital twins for use in conventional CT by planners at an operational level as a decision-support tool.
{"title":"Simulation-Based Optimization of Truck Appointment Systems in Container Terminals: A Dual Transactions Approach with Improved Congestion Factor Representation","authors":"Davies K. Bett, Islam Ali, M. Gheith, Amr Eltawil","doi":"10.3390/logistics8030080","DOIUrl":"https://doi.org/10.3390/logistics8030080","url":null,"abstract":"Background: Container terminals (CTs) have constantly administered truck appointment systems (TASs) to effectively accomplish the planning and scheduling of drayage operations. However, since the operations in the gate and yard area of a CT are stochastic, there is a need to incorporate uncertainty during the development and execution of appointment schedules. Further, the situation is complicated by disruptions in the arrival of external trucks (ETs) during transport, which results in congestion at the port due to unbalanced arrivals. In the wake of Industry 4.0, simulation can be used to test and investigate the present CT configurations for possible improvements. Methods: This paper presents a simulation optimization (SO) and simulation-based optimization (SBO) iteration framework which adopts a dual transactions approach to minimize the gate operation costs and establish the relationship between productivity and service time while considering congestion in the yard area. It integrates the use of both the developed discrete event simulation (DES) and a mixed integer programming (MIP) model from the literature to iteratively generate an improved schedule. The key performance indicators considered include the truck turnaround time (TTT) and the average time the trucks spend at each yard block (YB). The proposed approach was verified using input parameters from the literature. Results: The findings from the SO experiments indicate that, at most, two gates were required to be opened at each time window (TW), yielding an average minimum operating cost of USD 335.31. Meanwhile, results from the SBO iteration experiment indicate an inverse relationship between productivity factor (PF) values and yard crane (YC) service time. Conclusions: Overall, the findings provided an informed understanding of the need for dynamic scheduling of available resources in the yard to cut down on the gate operating costs. Further, the presented two methodologies can be incorporated with Industry 4.0 technologies to design digital twins for use in conventional CT by planners at an operational level as a decision-support tool.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":"19 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141923148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.3390/logistics8030075
A. Zaid, Ahmed R. Asaad, Mohammed Othman, Ahmad Haj Mohammad
Background: This research aims to solve a home healthcare vehicle routing problem (HHCVRP) model that considers the social aspect of sustainability and will be implemented in smart cities. In addition to the dynamism and uncertainty caused by variations in the patient’s condition, the proposed model considers parameters and variables that enhance its practicability, such as assuming different levels of patient importance (priority). Methods: The model was solved using a metaheuristic algorithm approach via the Ant Colony Optimization algorithm and the Non-Dominated Sorting technique due to the ability of such a combination to work out with dynamic models with uncertainties and multi-objectives. Results: This study proposes a novel mathematical model by integrating body sensors on patients to keep updating their conditions and prioritizing critical conditions in service. The sensitivity analysis demonstrates that using a heart rate sensor improves service quality and patient satisfaction without affecting the energy consumed. In addition, quality costs are increased if the importance levels of patients increase. Conclusions: The suggested model can assist healthcare practitioners in tracking patients’ health conditions to improve the quality of service and manage workload effectively. A trade-off between patient satisfaction and service provider satisfaction should be maintained.
{"title":"Multi-Objective Technology-Based Approach to Home Healthcare Routing Problem Considering Sustainability Aspects","authors":"A. Zaid, Ahmed R. Asaad, Mohammed Othman, Ahmad Haj Mohammad","doi":"10.3390/logistics8030075","DOIUrl":"https://doi.org/10.3390/logistics8030075","url":null,"abstract":"Background: This research aims to solve a home healthcare vehicle routing problem (HHCVRP) model that considers the social aspect of sustainability and will be implemented in smart cities. In addition to the dynamism and uncertainty caused by variations in the patient’s condition, the proposed model considers parameters and variables that enhance its practicability, such as assuming different levels of patient importance (priority). Methods: The model was solved using a metaheuristic algorithm approach via the Ant Colony Optimization algorithm and the Non-Dominated Sorting technique due to the ability of such a combination to work out with dynamic models with uncertainties and multi-objectives. Results: This study proposes a novel mathematical model by integrating body sensors on patients to keep updating their conditions and prioritizing critical conditions in service. The sensitivity analysis demonstrates that using a heart rate sensor improves service quality and patient satisfaction without affecting the energy consumed. In addition, quality costs are increased if the importance levels of patients increase. Conclusions: The suggested model can assist healthcare practitioners in tracking patients’ health conditions to improve the quality of service and manage workload effectively. A trade-off between patient satisfaction and service provider satisfaction should be maintained.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":"15 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141813498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-18DOI: 10.3390/logistics8030074
I. Masudin, Isna Zahrotul Habibah, Rahmad Wisnu Wardana, D. Restuputri, S. R. Shariff
Background: This research endeavors to enhance supplier selection processes by combining the Analytic Network Process (ANP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodologies, with a specific focus on sustainability criteria. Method: Initially comprising 21 sub-criteria derived from prior research, the selection criteria are refined to 17, eliminating redundant elements. The core principle guiding this refinement is the comprehensive coverage of economic, social, and environmental dimensions, essential for sustainable supplier evaluation. Results: The study’s outcomes underscore the paramount importance of economic criteria (0.0652) in supplier selection, followed by environmental (0.0343) and social dimensions (0.0503). Key sub-criteria contributing significantly to this evaluation encompassed consistent product quality, competitive raw material pricing, proficient labor capabilities, recycling potential, punctual delivery performance, and effective waste management practices. Conclusions: These sub-criteria are thoughtfully integrated into the sustainable assessment framework, aligning seamlessly with the economic, environmental, and social criteria.
{"title":"Enhancing Supplier Selection for Sustainable Raw Materials: A Comprehensive Analysis Using Analytical Network Process (ANP) and TOPSIS Methods","authors":"I. Masudin, Isna Zahrotul Habibah, Rahmad Wisnu Wardana, D. Restuputri, S. R. Shariff","doi":"10.3390/logistics8030074","DOIUrl":"https://doi.org/10.3390/logistics8030074","url":null,"abstract":"Background: This research endeavors to enhance supplier selection processes by combining the Analytic Network Process (ANP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodologies, with a specific focus on sustainability criteria. Method: Initially comprising 21 sub-criteria derived from prior research, the selection criteria are refined to 17, eliminating redundant elements. The core principle guiding this refinement is the comprehensive coverage of economic, social, and environmental dimensions, essential for sustainable supplier evaluation. Results: The study’s outcomes underscore the paramount importance of economic criteria (0.0652) in supplier selection, followed by environmental (0.0343) and social dimensions (0.0503). Key sub-criteria contributing significantly to this evaluation encompassed consistent product quality, competitive raw material pricing, proficient labor capabilities, recycling potential, punctual delivery performance, and effective waste management practices. Conclusions: These sub-criteria are thoughtfully integrated into the sustainable assessment framework, aligning seamlessly with the economic, environmental, and social criteria.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":" 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141826293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As global supply chains face increasing complexity, the demand for agile and sustainable management strategies has become more critical. This study employs advanced machine learning (ML) techniques to transform logistics and inventory management, moving beyond the constraints of traditional analytical methods. Utilizing historical data from a multinational retail corporation, including sales, inventory levels, order fulfillment rates, and operational costs, we have applied a range of ML algorithms such as regression, classification, clustering, and time series analysis. These models were developed to tackle key operational challenges, enhancing decision-making by improving demand forecasting accuracy by 15%, optimizing stock levels by reducing overstock and stockouts by 10%, and predicting order fulfillment timelines with 95% accuracy. Additionally, our approach enabled the identification of at-risk shipments and the segmentation of customers based on their delivery preferences, facilitating personalized service offerings. A comprehensive evaluation of these models showed significant improvements in predictive accuracy, efficiency in lead time by 12%, silhouette coefficients for clustering at 0.75, and a reduction in replenishment errors by 8%, highlighting the transformative potential of ML in making supply chain operations more responsive and data driven.
随着全球供应链面临的复杂性不断增加,对敏捷和可持续管理战略的需求变得更加迫切。本研究采用先进的机器学习(ML)技术来改变物流和库存管理,超越了传统分析方法的限制。利用一家跨国零售公司的历史数据,包括销售额、库存水平、订单执行率和运营成本,我们应用了一系列 ML 算法,如回归、分类、聚类和时间序列分析。开发这些模型的目的是应对关键的运营挑战,通过将需求预测准确率提高 15%、通过将超储和缺货率降低 10%来优化库存水平,以及以 95% 的准确率预测订单执行时间表,从而增强决策能力。此外,我们的方法还能识别风险货物,并根据客户的交付偏好对其进行细分,从而促进个性化服务的提供。对这些模型的综合评估显示,预测准确率有了显著提高,提前期效率提高了 12%,聚类的剪影系数达到了 0.75,补货错误减少了 8%,这凸显了人工智能在提高供应链运营响应速度和数据驱动力方面的变革潜力。
{"title":"Enhancing Supply Chain Agility and Sustainability through Machine Learning: Optimization Techniques for Logistics and Inventory Management","authors":"Vikram Pasupuleti, Bharadwaj Thuraka, Chandra Shikhi Kodete, Saiteja Malisetty","doi":"10.3390/logistics8030073","DOIUrl":"https://doi.org/10.3390/logistics8030073","url":null,"abstract":"As global supply chains face increasing complexity, the demand for agile and sustainable management strategies has become more critical. This study employs advanced machine learning (ML) techniques to transform logistics and inventory management, moving beyond the constraints of traditional analytical methods. Utilizing historical data from a multinational retail corporation, including sales, inventory levels, order fulfillment rates, and operational costs, we have applied a range of ML algorithms such as regression, classification, clustering, and time series analysis. These models were developed to tackle key operational challenges, enhancing decision-making by improving demand forecasting accuracy by 15%, optimizing stock levels by reducing overstock and stockouts by 10%, and predicting order fulfillment timelines with 95% accuracy. Additionally, our approach enabled the identification of at-risk shipments and the segmentation of customers based on their delivery preferences, facilitating personalized service offerings. A comprehensive evaluation of these models showed significant improvements in predictive accuracy, efficiency in lead time by 12%, silhouette coefficients for clustering at 0.75, and a reduction in replenishment errors by 8%, highlighting the transformative potential of ML in making supply chain operations more responsive and data driven.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":" 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141829087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-16DOI: 10.3390/logistics8030072
Michael Haughton, Alireza Amini
Background: One of several logistics contexts in which pricing decisions are made involves truckload carriers using reverse auctions to bid for prices they want for their transportation services while operating under uncertainty about factors such as their (i) operations costs and (ii) rivals’ bids. This study’s main purpose is to explore humans’ use of fast and frugal heuristics (FFHs) to navigate those uncertainties. In particular, the study clarifies the logic, theoretical underpinnings, and performance of human FFHs. Methods: The study uses behavior experiments as its core research method. Results: The study’s key findings are that humans use rational FFHs, yet, despite the rationality, human decisions yield average profits that are 35% below profits from price optimization models. The study also found that human FFHs yield very unstable outcomes: the FFH coefficient of variation in profit is twice as large as price optimization. Novel contributions inherent in these findings include (a) clarifying connections between spot market auction pricing and behavioral theories and (b) adding truckload spot markets to the literature’s contexts for measuring performance gaps between human FFHs and optimization models. Conclusions: The contributions have implications for practical purposes that include gauging spot pricing decisions made under constraints such as limited access to price optimization tools.
{"title":"An Examination of Human Fast and Frugal Heuristic Decisions for Truckload Spot Pricing","authors":"Michael Haughton, Alireza Amini","doi":"10.3390/logistics8030072","DOIUrl":"https://doi.org/10.3390/logistics8030072","url":null,"abstract":"Background: One of several logistics contexts in which pricing decisions are made involves truckload carriers using reverse auctions to bid for prices they want for their transportation services while operating under uncertainty about factors such as their (i) operations costs and (ii) rivals’ bids. This study’s main purpose is to explore humans’ use of fast and frugal heuristics (FFHs) to navigate those uncertainties. In particular, the study clarifies the logic, theoretical underpinnings, and performance of human FFHs. Methods: The study uses behavior experiments as its core research method. Results: The study’s key findings are that humans use rational FFHs, yet, despite the rationality, human decisions yield average profits that are 35% below profits from price optimization models. The study also found that human FFHs yield very unstable outcomes: the FFH coefficient of variation in profit is twice as large as price optimization. Novel contributions inherent in these findings include (a) clarifying connections between spot market auction pricing and behavioral theories and (b) adding truckload spot markets to the literature’s contexts for measuring performance gaps between human FFHs and optimization models. Conclusions: The contributions have implications for practical purposes that include gauging spot pricing decisions made under constraints such as limited access to price optimization tools.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":" 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141831876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-15DOI: 10.3390/logistics8030071
Nistor Andrei, Cezar Scarlat, Alexandra Ioanid
The logistics landscape in e-commerce is undergoing a profound transformation toward sustainability and autonomy. This paper explores the implementation of autonomous maritime and last-mile transportation solutions to optimize the entire logistics chain from factory to customer. Building on the lessons learned from the maritime industry’s digital transformation, the study identifies key features and proposes a forward-looking autonomous maritime and last-mile transportation system. Emphasizing the role of geospatial technologies, the proposed system employs GIS-based electronic route optimization for efficient goods delivery, integrating onboard and ashore GIS-based sensors for enhanced location precision. A case study was built to analyze the implementation of autonomous means of transport along the route of a product from factory to customer. The integration of autonomous systems shows substantial improvements in logistics performance. Synchromodal logistics and smart steaming techniques can be utilized to optimize transportation routes, resulting in reduced fuel consumption and emissions. The findings reveal that autonomous maritime and last-mile transport systems can significantly enhance the efficiency, flexibility and sustainability of e-commerce logistics. The study emphasizes the need for advanced technological integration and provides a comprehensive framework for future research and practical applications in the logistics industry.
{"title":"Transforming E-Commerce Logistics: Sustainable Practices through Autonomous Maritime and Last-Mile Transportation Solutions","authors":"Nistor Andrei, Cezar Scarlat, Alexandra Ioanid","doi":"10.3390/logistics8030071","DOIUrl":"https://doi.org/10.3390/logistics8030071","url":null,"abstract":"The logistics landscape in e-commerce is undergoing a profound transformation toward sustainability and autonomy. This paper explores the implementation of autonomous maritime and last-mile transportation solutions to optimize the entire logistics chain from factory to customer. Building on the lessons learned from the maritime industry’s digital transformation, the study identifies key features and proposes a forward-looking autonomous maritime and last-mile transportation system. Emphasizing the role of geospatial technologies, the proposed system employs GIS-based electronic route optimization for efficient goods delivery, integrating onboard and ashore GIS-based sensors for enhanced location precision. A case study was built to analyze the implementation of autonomous means of transport along the route of a product from factory to customer. The integration of autonomous systems shows substantial improvements in logistics performance. Synchromodal logistics and smart steaming techniques can be utilized to optimize transportation routes, resulting in reduced fuel consumption and emissions. The findings reveal that autonomous maritime and last-mile transport systems can significantly enhance the efficiency, flexibility and sustainability of e-commerce logistics. The study emphasizes the need for advanced technological integration and provides a comprehensive framework for future research and practical applications in the logistics industry.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":"9 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141646720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.3390/logistics8030070
Abdulaziz Aljoghaiman, Ahmed M. Hasanein, I. Elshaer, A. Sobaih
Background: This research examines the direct influence of green supply chain management (GSCM) on hotel competitiveness and the indirect impact through environmental performance (EP). The competition between enterprises in today’s changing marketplace has significantly heightened. Therefore, identifying the factors that contribute to an enterprises’ competitiveness has become more essential than it was previously. Methods: We adopted a pre-tested scale drawn from previous related studies and we were able to collect 430 forms from managers and department heads in Saudi Arabian hotels. Results: The study findings of the structural model by PLS-SEM revealed that environmental and economic GSCM had a considerable beneficial influence on hotel competitiveness. However, the social aspect of GSCM failed to have an extensive effect on hotel competitiveness. All three dimensions of GSCM have a substantial indirect influence on hotel competitiveness via EP. Conclusion: The study developed a complete model that integrates the elements of GSCM with EP and hotel competitiveness. The study presents numerous implications for hoteliers and academics.
{"title":"Does Environmental Performance Make Any Difference in the Relationship between Green Supply Chain Management and Hotel Competitiveness?","authors":"Abdulaziz Aljoghaiman, Ahmed M. Hasanein, I. Elshaer, A. Sobaih","doi":"10.3390/logistics8030070","DOIUrl":"https://doi.org/10.3390/logistics8030070","url":null,"abstract":"Background: This research examines the direct influence of green supply chain management (GSCM) on hotel competitiveness and the indirect impact through environmental performance (EP). The competition between enterprises in today’s changing marketplace has significantly heightened. Therefore, identifying the factors that contribute to an enterprises’ competitiveness has become more essential than it was previously. Methods: We adopted a pre-tested scale drawn from previous related studies and we were able to collect 430 forms from managers and department heads in Saudi Arabian hotels. Results: The study findings of the structural model by PLS-SEM revealed that environmental and economic GSCM had a considerable beneficial influence on hotel competitiveness. However, the social aspect of GSCM failed to have an extensive effect on hotel competitiveness. All three dimensions of GSCM have a substantial indirect influence on hotel competitiveness via EP. Conclusion: The study developed a complete model that integrates the elements of GSCM with EP and hotel competitiveness. The study presents numerous implications for hoteliers and academics.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":"118 33","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141656774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-08DOI: 10.3390/logistics8030069
German Pantoja-Benavides, Daniel Giraldo, A. Montes, Andrea García, Carlos Rodríguez, César Marín, David Álvarez-Martínez
Background: This review addresses the emerging field of automated packing cells, which lies at the intersection of robotics and packing problems. Integrating these two fields is critical for optimizing logistics and e-commerce operations. The current literature focuses on packing problems or specific robotic applications without addressing their integration. Methods: To bridge this gap, we conducted a comprehensive review of 46 relevant studies, analyzing various dimensions, including the components of robotic packing cells, the types of packing problems, the solution approaches, and performance comparisons. Results: Our review reveals a significant trend towards addressing online packing problems, which reflects the dynamic nature of logistics operations where item information is often incomplete. We also identify several research gaps, such as the need for standardized terminologies, comprehensive methodologies, and the consideration of real-world constraints in robotic algorithms. Conclusions: This review uniquely integrates insights from robotics and packing problems, providing a structured framework for future research. It highlights the importance of considering practical robotic constraints. It proposes a research structure that enhances the reproducibility and comparability of results in real-world scenarios. By doing so, we aim to guide future research efforts and facilitate the development of more robust and practical automated packing systems.
{"title":"Comprehensive Review of Robotized Freight Packing","authors":"German Pantoja-Benavides, Daniel Giraldo, A. Montes, Andrea García, Carlos Rodríguez, César Marín, David Álvarez-Martínez","doi":"10.3390/logistics8030069","DOIUrl":"https://doi.org/10.3390/logistics8030069","url":null,"abstract":"Background: This review addresses the emerging field of automated packing cells, which lies at the intersection of robotics and packing problems. Integrating these two fields is critical for optimizing logistics and e-commerce operations. The current literature focuses on packing problems or specific robotic applications without addressing their integration. Methods: To bridge this gap, we conducted a comprehensive review of 46 relevant studies, analyzing various dimensions, including the components of robotic packing cells, the types of packing problems, the solution approaches, and performance comparisons. Results: Our review reveals a significant trend towards addressing online packing problems, which reflects the dynamic nature of logistics operations where item information is often incomplete. We also identify several research gaps, such as the need for standardized terminologies, comprehensive methodologies, and the consideration of real-world constraints in robotic algorithms. Conclusions: This review uniquely integrates insights from robotics and packing problems, providing a structured framework for future research. It highlights the importance of considering practical robotic constraints. It proposes a research structure that enhances the reproducibility and comparability of results in real-world scenarios. By doing so, we aim to guide future research efforts and facilitate the development of more robust and practical automated packing systems.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":" 923","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141668980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-05DOI: 10.3390/logistics8030068
G. Bilek, Richard Calvi, Daniel Erhel, Youcef Mechouar
Background: The role of individual supply chain actors in carbon emissions reduction (CER) is well-documented. However, it is critical to identify the conditions required to develop a systemic approach for encouraging these actors to share their visions and align their environmental strategy for CER. This study aims to identify the determinants (motivations, pressures, and incentives) and modalities (practices conducting greening transportation from shippers and logistics service providers (LSP) point of view) necessary for a better environmental alignment between actors for a CER initiative. Methods: We base our argument on a systemic literature review that points out 28 articles written in the period between 2010 and 2023 and fully aligned with the scope of our analysis. Results: The originality of our approach is that we focus on the interplay between shippers and LSPs to better understand the dynamics of green transportation practices. Conclusions: This paper invites researchers to adopt a dyadic approach to the phenomenon in order to better understand how the CER willingness is effectively diffused in the business interactions of shippers and LSP.
{"title":"Towards Green Transportation Practices Using a Buyer/Supplier Perspective: A Systematic Literature Review","authors":"G. Bilek, Richard Calvi, Daniel Erhel, Youcef Mechouar","doi":"10.3390/logistics8030068","DOIUrl":"https://doi.org/10.3390/logistics8030068","url":null,"abstract":"Background: The role of individual supply chain actors in carbon emissions reduction (CER) is well-documented. However, it is critical to identify the conditions required to develop a systemic approach for encouraging these actors to share their visions and align their environmental strategy for CER. This study aims to identify the determinants (motivations, pressures, and incentives) and modalities (practices conducting greening transportation from shippers and logistics service providers (LSP) point of view) necessary for a better environmental alignment between actors for a CER initiative. Methods: We base our argument on a systemic literature review that points out 28 articles written in the period between 2010 and 2023 and fully aligned with the scope of our analysis. Results: The originality of our approach is that we focus on the interplay between shippers and LSPs to better understand the dynamics of green transportation practices. Conclusions: This paper invites researchers to adopt a dyadic approach to the phenomenon in order to better understand how the CER willingness is effectively diffused in the business interactions of shippers and LSP.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":" 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-03DOI: 10.3390/logistics8030067
Eduard Klundt, Neil Towers, Kamal Bechkoum
Background: This paper examines how logistics mangers increase performance by incorporating VAS in their distribution centres in the context of different natures of customer demand. The study is underpinned by the principles of lean and agile strategies as two key concepts that can be applied to respond to different customer expectations. Methods: Based on the phenomenological interpretivist paradigm, an empirical multiple-case study was conducted in German distribution centres operated by six companies. The empirical data were collected through semi-structured interviews, built on the triangulation of sources. Open, axial, and selective coding were employed to analyse data collected through eighteen in-depth interviews with managers from the distribution centres. Results: The findings indicated that the construct of customer demand forms different benefits that the logistics service providers can achieve through VAS. Simultaneously, various customer demands on VAS requires the distribution centres to focus on developing different operational capabilities to gain superior performance. Conclusions: Based on the research findings, a conceptual model was created. This model can support logistics service providers in improving company performance through effectively managing VAS in their distribution centres. The high dynamic VAS customer demand can bring more financial and non-financial benefits but needs higher flexibility in the warehouse operation system. Stable and predictable VAS, in turn, require a higher degree of standardisation.
{"title":"Lean and Agile Supply Strategies in Distribution Centres to Deliver Value-Added Services (VAS)","authors":"Eduard Klundt, Neil Towers, Kamal Bechkoum","doi":"10.3390/logistics8030067","DOIUrl":"https://doi.org/10.3390/logistics8030067","url":null,"abstract":"Background: This paper examines how logistics mangers increase performance by incorporating VAS in their distribution centres in the context of different natures of customer demand. The study is underpinned by the principles of lean and agile strategies as two key concepts that can be applied to respond to different customer expectations. Methods: Based on the phenomenological interpretivist paradigm, an empirical multiple-case study was conducted in German distribution centres operated by six companies. The empirical data were collected through semi-structured interviews, built on the triangulation of sources. Open, axial, and selective coding were employed to analyse data collected through eighteen in-depth interviews with managers from the distribution centres. Results: The findings indicated that the construct of customer demand forms different benefits that the logistics service providers can achieve through VAS. Simultaneously, various customer demands on VAS requires the distribution centres to focus on developing different operational capabilities to gain superior performance. Conclusions: Based on the research findings, a conceptual model was created. This model can support logistics service providers in improving company performance through effectively managing VAS in their distribution centres. The high dynamic VAS customer demand can bring more financial and non-financial benefits but needs higher flexibility in the warehouse operation system. Stable and predictable VAS, in turn, require a higher degree of standardisation.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":"97 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141682896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}