This study aims to design and implement a web-based shipment information system integrated with barcode technology to improve the efficiency and accuracy of goods delivery management at PT. Anugerah Fajar. The existing shipment management process relied heavily on manual recording methods, which resulted in data entry errors, delays in updating shipment status, and limited visibility of goods in transit. To address these issues, a barcode-based information system was developed to automate shipment identification, tracking, and reporting processes. The system was developed using the Rapid Application Development (RAD) methodology, which emphasizes iterative development and active user involvement. Data were collected through direct observation, interviews with administrative and field personnel, documentation analysis, and literature review. The proposed system includes core features such as user authentication, shipment data management, barcode scanning using one-dimensional (1D) barcodes, real-time shipment status updates, report generation, and system configuration. The results show that the implemented system successfully improves operational efficiency by reducing manual data entry and minimizing human errors in shipment recording. Real-time barcode scanning enables faster and more accurate shipment status updates, enhancing transparency and control throughout the distribution process. Additionally, the dashboard and reporting features support effective monitoring, documentation, and managerial decision-making. The findings indicate that integrating barcode technology into a web-based shipment information system provides a practical and scalable solution for modern logistics management. This research contributes to the field of information systems by demonstrating the effectiveness of barcode-based digital solutions in improving logistics operations within distribution companies.
Purpose The purpose of this paper is to present the design and implementation of a genetic algorithm (GA), using a large language model (LLM) for optimizing the delivery scheduling process in warehouses of third-party logistics (3PL) companies, within the context of a simplified case study, and to highlight the main directions for implementing this methodology in business realities. Design/methodology/approach Using a simplified case study of an international 3PL company, this study applies a GA developed in RStudio by LLM to generate test scenarios and input data. The GA was optimized to minimize the time and distance of movement in the process of preparing goods for shipment, demonstrating its effectiveness in improving warehouse delivery scheduling. Findings The study confirms that the GA, supported by LLM, significantly improves the delivery planning process in the warehouse. Specifically, the implementation of the GA led to notable improvements in scheduling efficiency and a reduction in the distance traveled within the warehouse. These enhancements enable more efficient generation, evaluation and optimization of logistic scenarios. Additionally, the use of LLM greatly facilitates the creation and refinement of complex algorithms like GA, through automation and innovative approaches in logistics. Research limitations/implications The study highlights limitations related to data quality, the dynamic nature of logistic operations, computational complexity and the need for generalization of results. It also points out the lack of research in business realities that demonstrate the effectiveness of combining the benefits of LLM and GA in practice. Originality/value This paper makes a significant contribution to the literature by demonstrating the capabilities of advanced technologies such as GA and LLM in 3PL logistics. It presents an innovative approach to optimizing logistic processes, offering perspectives for further innovations and automation in supply chain management. It also indicates new opportunities for 3PL companies in terms of improving operational and cost efficiency, emphasizing the importance of continuously seeking innovative solutions in the face of increasing market demands.
This study aims to develop a web-based goods delivery monitoring application using PHP, MySQL, and Bootstrap to address the issues of limited visibility and real-time monitoring in the goods delivery process. The application provides real-time tracking features, shipment activity log recording, and a responsive interface, making it easily accessible across various devices. Bootstrap is employed to create a modern and user-friendly interface, while PHP and MySQL support the management of large and complex data. The research results indicate that this application successfully fills the gaps found in previous studies, particularly in terms of real-time monitoring and responsive design. With these features, the application can improve operational efficiency, reduce errors in the delivery process, and provide better transparency for users. Overall, this research contributes to the development of logistics information systems, especially in optimizing goods delivery management to be more efficient and user-friendly.
An emerging type of fraud involves malicious senders exploiting the blind shipment and cash-on-delivery (COD) mechanisms by dispatching large volumes of unsolicited, low-cost parcels. If unsuspecting receivers accept these parcels, they pay for both shipping and goods; otherwise, logistics providers bear the round-trip shipping costs. Existing detection techniques, which rely on extensive labeled cases, struggle with this emerging fraud because receivers' unawareness and low transaction values discourage complaints, resulting in few confirmed cases. Therefore, we propose leveraging receivers' complaints, though not initially collected for fraud detection, to uncover subtle indicators of fraud patterns, while addressing three challenges: (C1) noise-rich dialogues(C2) data privacy concerns, and (C3) ever-evolving fraud patterns. To address them, we design BLOFF, a Blind shipment detection Framework for LO gistics Fraud powered by large language models (LLMs). Specifically, BLOFF includes three components: i) Sensitivity Anonymization to protect sensitive user information; ii) Dialogue Profile Distillation to transform informal dialogues into structured representation, addressing C1, and distill knowledge from a teacher LLM (GPT-4o) to a lightweight student LLM (ChatGLM4-9B), addressing C2; ii) Multi-faceted Context Augmentation to enhance the interpretation of fraud signatures and adaptation of evolving patterns, addressing C3. We evaluate BLOFF on about 56,000 complaints records collected from JD Logistics between January and November 2024. Results show that BLOFF outperforms state-of-the-art methods, achieving a 10.19% improvement in precision. Furthermore, during its real-world deployment in December 2024, BLOFF identified over 90 fraudulent parcels with a 91.4% precision.
Developing policy instruments related to urban freight, such as congestion pricing, urban consolidation schemes, and off-hours delivery, requires an understanding of the distribution of shipment delivery times. Furthermore, agent-based urban freight simulators use relevant information (shipment delivery time distribution or vehicle tour start time distribution) as input to simulate tour generation. However, studies focusing on shipment delivery time-period selection modeling are very limited. In this study, we propose a method using GPS trajectory data from the Tokyo Metropolitan Area to estimate a shipment delivery time-period selection model based on pseudo-shipment records inferred from GPS data. The results indicate that shipment distance, size, and destination attributes can explain the delivery times of goods. Moreover, we demonstrate the practicality of the model by comparing the simulation result with the observed data for three areas with distinct characteristics, concluding that the model could be applied to urban freight simulation models for accurately reproducing spatial heterogeneity in shipment delivery time periods. This study contributes to promoting smart city development and management by proposing a method to use big data to better understand deliveries and support the development of relevant advanced city logistics solutions.
The relocation of containers is essential at port terminals to increase operational efficiency during container retrieval from the yard. When a container must be retrieved, any container placed on top of it must be moved to another stack, delaying the retrieval process. The container premarshalling problem (CPMP) aims to tackle this issue by finding a sequence of minimal container relocations to achieve a bay arrangement where no container needs to be moved during retrieval. The classical formulation of this problem assumes that all premarshalling relocations occur within the bay being arranged. However, this study demonstrates that practical applications of premarshalling can benefit from more efficient use of available resources. We introduce a novel problem variant that allows the use of an auxiliary bay as additional space for relocating containers during the arrangement process. We present constraint programming solution methods for this variant that reveal a significant reduction in premarshalling relocations when an auxiliary bay is used. The results demonstrate that bays where high occupancy rates prevent premarshalling can be successfully arranged with an auxiliary bay. Additionally, we propose two alternative formulations allowing different rates of relocations between bays, offering adaptability to varying port terminal requirements.
Abstract Maritime piracy has severely disrupted Nigeria’s maritime domain, undermining the numerous benefits promised by the African Continental Free Trade Agreement (AfCFTA) and posing a significant threat to its successful implementation. As this study highlights, maritime piracy in Nigeria emerges partly as a deviant response to the socio-economic pressures intensified by neoliberalism and globalization. By examining maritime piracy through the lens of Global Anomie Theory (GAT) and civic governance frameworks – supplemented by insights from interviewees – this research offers a deeper understanding of how such criminal activities could jeopardize Nigeria’s ability to fully realize the objectives of the AfCFTA. In doing so, it contributes to the growing body of literature on the intersection of free trade agreements and maritime security challenges. Given the AfCFTA protocols that emphasize Member States’ responsibilities to safeguard their security interests, this study argues that Nigeria must extend its anti-piracy strategies beyond domestic initiatives. Specifically, it recommends that Nigeria strengthen international cooperation mechanisms as a critical step toward ensuring the effective implementation of the AfCFTA agreement.
Shipment of goods. Delivery of goods, Transportation and communications
O Conhecimento de Embarque Marítimo (Bill of Lading - B/L) é um documento multifuncional essencial no transporte internacional de cargas, possuindo funções de contrato, recibo e título de crédito impróprio. Este estudo investiga sua evolução histórica, desde as origens no período romano até sua forma moderna, além de analisar a regulação brasileira em comparação com normas internacionais, como as Regras de Haia e Hamburgo. O problema de pesquisa busca compreender os desafios jurídicos e operacionais do B/L no Brasil e sua adequação às demandas do comércio global. O objetivo geral é avaliar sua relevância histórica, jurídica e prática, enquanto os objetivos específicos incluem: explorar suas origens, examinar sua regulação no Brasil, identificar suas funções e natureza jurídica tríplice e avaliar os desafios em sua aplicação no transporte marítimo e aduana. A metodologia utilizada é qualitativa, baseada em pesquisa bibliográfica e documental, com análise de legislações e estudos de caso relevantes. A pesquisa demonstra que, apesar de sua evolução significativa, o B/L enfrenta desafios no Brasil devido a lacunas normativas e questões práticas que impactam a segurança jurídica e eficiência no comércio internacional.
Accurate prediction of food delivery times significantly impacts customer satisfaction, operational efficiency, and profitability in food delivery services. However, existing studies primarily utilize static historical data and often overlook dynamic, real-time contextual factors crucial for precise prediction, particularly in densely populated Indian cities. This research addresses these gaps by integrating real-time contextual variables such as traffic density, weather conditions, local events, and geospatial data (restaurant and delivery location coordinates) into predictive models. We systematically compare various machine learning algorithms, including Linear Regression, Decision Trees, Bagging, Random Forest, XGBoost, and LightGBM, on a comprehensive food delivery dataset specific to Indian urban contexts. Rigorous data preprocessing and feature selection significantly enhanced model performance. Experimental results demonstrate that the LightGBM model achieves superior predictive accuracy, with an R2 score of 0.76 and Mean Squared Error (MSE) of 20.59, outperforming traditional baseline approaches. Our study thus provides actionable insights for improving logistics strategies in complex urban environments. The complete methodology and code are publicly available for reproducibility and further research.
In the era of globalization, efficient cargo shipment management is crucial for optimizing global logistics operations. This paper proposes an IoT-enabled system for real-time tracking and optimization of cargo shipments. By integrating IoT sensors, RFID technology, GPS, and data analytics, the system provides continuous monitoring of cargo conditions such as location, temperature, humidity, and security, ensuring optimal environmental conditions throughout the shipment journey. The proposed system enhances operational efficiency by enabling real-time data collection, predictive analytics, and dynamic route optimization, reducing costs and improving delivery reliability. Furthermore, IoT integration facilitates proactive decision-making, risk mitigation, and the prevention of theft or damage to goods. By streamlining logistics processes and providing actionable insights, this solution offers significant improvements in supply chain visibility, safety, and efficiency. The findings suggest that IoT-enabled cargo shipment management can revolutionize global logistics by enhancing transparency, reducing operational disruptions, and ensuring timely deliveries in the face of complex, multimodal transportation networks.
Understanding how cooperation emerges in public goods games is crucial for addressing societal challenges. While optional participation can establish cooperation without identifying cooperators, it relies on specific assumptions -- that individuals abstain and receive a non-negative payoff, or that non-participants cause damage to public goods -- which limits our understanding of its broader role. We generalize this mechanism by considering non-participants' payoffs and their potential direct influence on public goods, allowing us to examine how various strategic motives for non-participation affect cooperation. Using replicator dynamics, we find that cooperation thrives only when non-participants are motivated by individualistic or prosocial values, with individualistic motivations yielding optimal cooperation. These findings are robust to mutation, which slightly enlarges the region where cooperation can be maintained through cyclic dominance among strategies. Our results suggest that while optional participation can benefit cooperation, its effectiveness is limited and highlights the limitations of bottom-up schemes in supporting public goods.
Transportation services for cargo shipment is growing rapidly during the pandemic and the post pandemic of Covid-19. However, this business is not without problems. Security disturbances during the cargo shipment process are a major problem, and this often happens in Indonesia. For this reason, this research will build a smart security system using automation technology and based on the Internet of Things (IoT). The system is a Smart Lock installed on the cargo. This smart lock can be monitored remotely, such as opening or closing the lock and the condition of the cargo in the field. Only the cargo owner can open or close the cargo lock. In addition, this system is also equipped with temperature and humidity sensor to maintain the quality of the goods in the cargo. Cargo position, temperature and temperature data can be monitored via the website by the cargo owner. The results of this research will be useful for the security system and convenience of the cargo delivery process and the digitization process will be easier to do in the future.
The growing interest in unmanned aircrafts, quadcopters and other flying vehicles determines the need for dispatching incoming information flows from multiple users for the delivery of cargo by these flying vehicles. The issue of dispatching message flows is closely related to the choice of a model for the rational organization of processing such flows. Analyzing the latest research and publications in this area, I would like to point the work of B. P. Knysh " The method of the time distribution for the goods shipment by the means of unpiloted aerial vehicles based on a priority." But the such priority mass service system can guarantees that the only highest priority goods will be delivered in time. The purpose of this work is to describe a conceptual model of information flow pro-cessing in aircraft delivery systems using the discipline for the rational organization of information processing based on several characteristics. There are provides mathemati-cal model that allows determining the main characteristic of the service - function of the waiting time for processing of a message received in the data processing system(DPS) at the time t.
Aniza Nur Madyanti, Nessa Ananda, Monanda Wandita Rini
et al.
The information and data processing in logistics activities are necessary for improving company performance. One logistics activity that needs to be managed is the shipment of goods. Some companies manually record and store shipment data, facing issues related to accuracy and pace. This research aims to design a web-based goods delivery information system for recording, storing, processing, and reporting shipments swiftly and faultlessly. The system is designed using stages in the Waterfall model, including analysis of needs, design, coding, and testing. The result is a web-based goods delivery application that can manage shipment activity data automatically and in real-time, reducing errors in recording and processing time. The system can also generate shipping documents, such as waybills and invoices, automatically and can be printed directly. Furthermore, it provides automatic real-time shipment reports, allowing monitoring of delivery performance through a dashboard on the main page of the application. This information system can assist companies in managing shipment activities.
Yuan-Shyi Peter Chiu, Ya-Lei Lo, Tsu-Ming Yeh
et al.
The present work intends to optimize a hybrid delayed differentiation multiproduct economic production quantity-EPQ model with the scrap and end-products multi-shipment policy. Since the requirements of multi-goods have a standard part in common, our fabrication planning adopts a two-phase delayed differentiation strategy to make the standard components first and produce the finished multi-goods in the second phase. Implementing a partial subcontracting option (with the additional expense) for the standard parts helps us to expedite the required uptime in the first phase. A screening process identifies the faulty items that need to be removed to ensure the in-house production quality. A multi-shipment plan delivers the finished lot of end-products to clients in fixed time intervals. This study optimizes the overall operating expenses of this intra-supply chain system, including fabrication, delivery, and client stock holding, through our proposed modeling, formulation, and optimization procedure. In addition, this study gives a numerical demonstration of the obtained results’ applicability and usefulness to managerial decision-making.
Storage of finished goods is one of the important factors needed by a company, both offline and online manufacturing. The problem that often occurs is the lack of area and inadequate warehouse locations for storing finished goods. This problem is also found in the activities of storing finished goods in shipping expeditions. The condition of the warehouse which was initially less efficient was due to the location of the warehouse being less spacious, the absence of safety equipment and also areas prone to flooding. The goal to be achieved is to choose the optimal warehouse location from several existing alternatives. The method used is the Analytical Hierarchy Process (AHP) method to develop a hierarchy of logistics center location selection. Research variables using criteria include distance, cost, facilities, geographical position and warehouse area. The results of data processing produce the highest criterion weight value of 0.3228, namely the area of the warehouse and the smallest criterion weight of 0.0417, namely the cost criterion. In addition, the highest value of the work alternative is 0.4085 on the SPILL warehousing alternative and the smallest value is 0.2749 on the Rungkut Industri alternative.
Shivendra Saurav, Shubham Kumar Singh, Sriyansh Ghosh
et al.
Hyperlocal organizations provide purchasers with merchandise delivery and utility administrations. Merchandise delivery includes staple goods, food, prescriptions, and personal needs, while utility administrations include plumbing, home cleaning, yard care, electrical, and drainage. Each of these services and products is provided by an organization of individuals from businesses or neighborhoods. Hyperlocal administration stages enable eateries, lodging, discount food outlets, organic products or vegetables, fish, and meat, and other retailers to attract and manage customers effectively without worrying about shipment. Simple web connectivity and the proliferation of cell phones have significantly increased interest in hyperlocal administrations. Occupied way of life accelerates the growth of the online food and staples ordering market, which in turn accelerates the growth of hyperlocal services in the emerging online market.
Katrien Storms, Christa Sys, Thierry Vanelslander
et al.
Abstract Reduced free time and increased fees for demurrage and detention create organizational challenges with respect to intermodal transport. As a result, actors within the maritime supply chains are confronted with greater complexity and higher risk of costs; and, therefore, often fall back on transportation by truck to and from the hinterland. That is why the present research examines the impact of this evolution on the bottom line of the involved actors from a maritime supply chain perspective. The research approach consists of reviewing the relevant literature, analyzing the available sector data obtained through interviews and professional experience, and validating the proposed solutions. Starting from the research results, the problem-solving discussions resulted in the following top three as feasible solutions: digitalization, extra ‘free time’ for hinterland locations, and more attention during the negotiation process.
Shipment of goods. Delivery of goods, Transportation and communications
Our work departs from the original definition of the Pickup and Delivery Problem (PDP) and extends it by considering an interchange point (crossdock) where vehicles can exchange their goods with other vehicles in order to shorten their delivery routes and reduce their running times. Multiple operational constraints, such as time windows, vehicle capacities, and the synchronization of vehicles at the crossdock, are considered. In addition, the specific requirements of perishable goods, which should not be carried on long trips, are taken into account. Given this consideration, this study introduces the Pickup and Delivery Problem with Crossdock for Perishable Goods (PDPCDPG) and models it as a nonlinear programming problem. PDPCDPG is then reformulated to a MILP with the use of linearizations and its search space is tightened with the addition of valid inequalities that are employed when solving the problem to global optimality with Branch-and-Cut. Various computational experiments are conducted on benchmark instances found in the literature to assess the performance of our model. The results demonstrate the solution stability of the proposed approach. The proposed model aims to provide a practical and effective approach for transportation and logistics companies dealing with time-sensitive deliveries.