Cargo Location Research Articles

Fuzzy PID Control Design of Mining Electric Locomotive Based on Permanent Magnet Synchronous Motor

Achieving precise stopping of electric locomotives is crucial for the realization of intelligent and unmanned auxiliary transportation systems. Presently, human drivers play a central role in ensuring accurate stopping, presenting obstacles to automation and cargo location precision, especially within the coal mining sector. This article centers on achieving the precise stopping of electric locomotives under various conditions through the utilization of permanent magnet synchronous motor-driven locomotives. This approach introduces a novel stopping control method that integrates a fuzzy proportional–integral–derivative (F-PID) controller with a vector control model for permanent magnet synchronous motors (PMSM). Subsequently, we develop the F-PID controller using the PMSM technique, incorporating new fuzzy rules for each subsystem to enhance control accuracy and efficiency. Finally, extensive simulations and real-world experiments are conducted on an electric locomotive stopping test bed to validate the effectiveness of the proposed control method. The results show that the method consistently achieves precise stopping under diverse working conditions, with an error of less than 0.3 m, confirming its robustness and reliability.

Big Data Swarm Intelligence Optimization Algorithm Application in the Intelligent Management of an E-Commerce Logistics Warehouse

A dynamic mutation probability formula is utilized to optimize the model. In order to solve the logistics warehouse path problem, the ant colony optimization algorithm, optimized by a genetic algorithm, is employed to construct a logistics warehouse path optimization model. This model effectively optimizes the logistics warehouse paths. Test results comparing the convergence and distribution of non-inferior solutions demonstrated that the proposed model outperforms others in terms of convergence and non-inferior solution distribution. In practical logistics warehouse optimization, applying the proposed model to optimize cargo locations can significantly enhance the effectiveness of the objective function. The optimization resulted in improvements for all four objective functions related to cargo location, with reduction rates of 10.38%, 30.88%, 51.78%, and 88.49%, respectively. For the optimization of logistics warehouse paths, the original distance was 47.6m, which was reduced to 27.8m after optimization. Consequently, the picking distance decreased by 41.60%.

Stowage Planning System for Ferry Ro-Ro Ships Using Particle Swarm Optimization Method

Stowage planning involves distributing cargo on board a ship, including quantity, weight, and destination details. It consists of collecting cargo manifest data, planning cargo location on decks, and calculating stability until the vessel is declared safe for sailing. Finding the ideal solution to real-world situations in this stowage planning problem is challenging and frequently requires a very long computing period. The Particle Swarm Optimization (PSO) algorithm is one of the evolutionary algorithms known for its efficient performance. PSO has been extended to complex optimization problems due to its fast convergence and easy implementation. In this study, the Particle Swarm Optimization (PSO) method is implemented to automate stowage arrangements on ships considering three factors (width, length, and weight of the vehicle). This system was evaluated with KMP Legundi vehicle manifest data and four load cases of 12 different vehicle types that can be loaded on Ferry / Ro-Ro Ships. It provides complete vehicle layouts and allows interactive changes for stowage planners, ensuring speed and accuracy in arranging ship cargo.

Revealing Population Heterogeneity in Vesicle-Based Nanomedicines Using Automated, Single Particle Raman Analysis.

The intrinsic heterogeneity of many nanoformulations is currently challenging to characterize on both the single particle and population level. Therefore, there is great opportunity to develop advanced techniques to describe and understand nanomedicine heterogeneity, which will aid translation to the clinic by informing manufacturing quality control, characterization for regulatory bodies, and connecting nanoformulation properties to clinical outcomes to enable rational design. Here, we present an analytical technique to provide such information, while measuring the nanocarrier and cargo simultaneously with label-free, nondestructive single particle automated Raman trapping analysis (SPARTA). We first synthesized a library of model compounds covering a range of hydrophilicities and providing distinct Raman signals. These compounds were then loaded into model nanovesicles (polymersomes) that can load both hydrophobic and hydrophilic cargo into the membrane or core regions, respectively. Using our analytical framework, we characterized the heterogeneity of the population by correlating the signal per particle from the membrane and cargo. We found that core and membrane loading can be distinguished, and we detected subpopulations of highly loaded particles in certain cases. We then confirmed the suitability of our technique in liposomes, another nanovesicle class, including the commercial formulation Doxil. Our label-free analytical technique precisely determines cargo location alongside loading and release heterogeneity in nanomedicines, which could be instrumental for future quality control, regulatory body protocols, and development of structure-function relationships to bring more nanomedicines to the clinic.

Optimization of target acquisition and sorting for object-finding multi-manipulator based on open MV vision

Abstract To optimize the mechanical arm target capture and classification of the open multiple-view (MV) visualization program, the open MV visualization programming and deep learning detection method combined with the different capture strategies of robotic arm, a method to extend the research is proposed. For the proposed sorting robot’s multi-cargo grasping, the analysis required to detect a wide variety of goods in a storage environment that lacks color or structural features uniformly. On the basis of SSD target detection method regression, the object’s 3D position information is reconstructed by default preselected cell selection. 3D coordinate accuracy of binocular navigation system was verified as 8% when the target cargo location distance is more than 5 cm, and binoculars matching success rate is 89.7%. The success rate of Sorting and hoarding is increased from 6% to 85% by adding a change to the scoring points of the target products of uneven quality, with this we have achieved efficient and accurate import.

Research on finished product warehouse inventory based on spatial segmentation

This paper proposes a finished product elevated warehouse inventory based on space segmentation, which does not need to control the low storage capacity in advance, nor does it need to stop the inventory, and can use the stacker to carry out the handling task when it is idle. Taking the finished product elevated warehouse of 8 roadways and 9 floors as an example, the inventory work of two floors can be completed every working day, and the inventory work of the whole reservoir area can be completed in 4.5 working days. The first step is to complete the division of the roadway by layer, and then move the finished product pallets of the layer requiring inventory to other layers. After WMS completes the clearance and transportation of all finished product pallets of this layer, the warehouse management personnel will enter the warehouse to manually verify the retention of finished product pallets. This step can ensure that there are finished product pallets in the cargo location with information. Then cooperate with the comparison of finished product pallets in the delivery area of finished product warehouse to realize this step, which can ensure the consistency between information and physical objects. The results show that this inventory method can completely replace the existing complicated manual inventory business, effectively realize the inventory work of finished product elevated warehouse, and provide an accurate and efficient inventory scheme for similar logistics elevated warehouse.

Dynamic Optimization Strategy of Large Airport Cargo Location based on Virus Evolutionary Genetic Algorithm

The automated stereoscopic warehouse of large airport plays an important role in logistics, in which cargo access efficiency is the most important part. And cargo location optimization is an effective method to improve its efficiency. After comparing and analysing the structure and working characteristics of bulk cargo processing system in large airport cargo station, the dynamic optimization problem of the cargo location was modelled. The virus evolutionary genetic algorithm (VEGA) was selected for optimization simulation, and the time-consuming rule was designed according to the actual optimization conditions. A cargo location numbering rule based on time-consuming rule was designed according to the actual optimization conditions. Simulation results show that both the convergence and calculating speeds of the VEGA have been obviously improved compared with those of the traditional genetic algorithm, which can meet the actual needs of the field better.

Generating decision support for alarm processing in cold supply chains using a hybrid k-NN algorithm

Real-time temperature monitoring is necessary in cold pharmaceutical supply chains (SCs), where exposures to extreme temperatures can lead to product quality deterioration. Temperature alarms (TAs) triggered by the current rule-based systems still require lengthy examinations before a suitable corrective measure (CM) can be chosen. However, provision of additional information relevant to TAs can expedite the examination process.In the related areas of recommender systems and false alarm/anomaly detection, k-nearest neighbors (k-NN) algorithm has proven to be successful because of its interpretability and ease of use. However, in the context of TA processing, it may suffer from some inherent limitations (i.e., varying neighborhood radius, unreliable classifications in sparse and noisy regions, and blindness to natural class boundaries). To overcome these limitations, we propose a hybrid k-NN (Hk-NN) algorithm based on the principles of local similarity and neighborhood homogeneity. It incorporates a two-step voting procedure with an entropy-optimized k-NN radius, decision trees with k-constrained leaves, and nearest neighbor predictions.We investigate 16,525 comments by alarm personnel for TAs in a pharmaceutical SC and encode them in terms of deviation causes and CMs (target features). We use SC data on cargo location, SC phase, sensor role, and temperature characteristics as predictor features for TA similarity estimation. In eight experimental setups, Hk-NN consistently outperforms k-NN with an optimized k in terms of accuracy, balanced accuracy, macro-average precision, recall, and specificity. At the same time, Hk-NN refrains from predicting observations, for which k-NN’s accuracy is close to a random guess.

Research on Multi-dimensional Data Collaborative Virtual Inventory Based on Markov

The three-dimensional elevated warehouse is a production equipment, and it is inevitable that it will malfunction during the operation. If it is not handled properly, there will be inconsistencies between information and practice, resulting in inconsistency between inventory information and the actual product. In order to solve the above problems, this project team carried out functional research on various SQL tables of multi-dimensional data collaboration, and constructed a virtual inventory method based on Markov multi-dimensional data collaboration. The behavioral characteristics of the cargo location information in the cargo location table TWMS_LOC and the pallet status table TWMS_PLT are extracted, and the two are compared. If the deviation between the two exceeds the threshold, the status is judged to be no cargo information. Experiments are conducted to test the feasibility and effectiveness of the sentences of the proposed virtual inventory. The results show that the inventory method can better describe the status of the cargo location and information, and effectively realize the virtual inventory at the database level. The research results of this method will completely replace the complicated manual inventory business. It can provide accurate and efficient virtual inventory solutions for similar logistics elevated warehouses.

Cell trafficking and regulation of osteoblastogenesis by extracellular vesicle associated bone morphogenetic protein 2.

Extracellular vesicles (EVs) are characterized by complex cargo composition and carry a wide array of signalling cargo, including growth factors (GFs). Beyond surface‐associated GFs, it is unclear if EV intralumenal growth factors are biologically active. Here, bone morphogenetic protein‐2 (BMP2), loaded directly into the lumen of EVs designated engineered BMP2‐EVs (eBMP2‐EVs), was comprehensively characterized including its regulation of osteoblastogenesis. eBMP2‐EVs and non‐EV ‘free’ BMP2 were observed to similarly regulate osteoblastogenesis. Furthermore, cell trafficking experiments suggest rapid BMP2 recycling and its extracellular release as ‘free’ BMP2 and natural occurring BMP2‐EVs (nBMP2‐EVs), with both being osteogenic. Interestingly, BMP2 occurs on the EV surface of nBMP2‐EVs and is susceptible to proteolysis, inhibition by noggin and complete dissociation from nBMP2‐EVs over 3 days. Whereas, within the eBMP2‐EVs, BMP2 is protected from proteolysis, inhibition by noggin and is retained in EV lumen at 100% for the first 24 h and ∼80% after 10 days. Similar to ‘free’ BMP2, bioprinted eBMP2‐EV microenvironments induced osteogenesis in vitro and in vivo in spatial registration to the printed patterns. Taken together, BMP2 signalling involves dynamic BMP2 cell trafficking in and out of the cell involving EVs, with distinct differences between these nBMP2‐EVs and eBMP2‐EVs attributable to the BMP2 cargo location with EVs. Lastly, eBMP2‐EVs appear to deliver BMP2 directly into the cytoplasm, initiating BMP2 signalling within the cell, bypassing its cell surface receptors.

Optimization of warehouse management based on artificial intelligence technology

This paper analyzes the artificial intelligence algorithms related to the storage path optimization problem and focuses on the ant colony algorithm and genetic algorithm with better applicability. The genetic algorithm is used to optimize the parameters of the ant colony algorithm, and the performance of the ant colony algorithm is improved. A typical route optimization problem model is taken as an example to prove the effectiveness of parameter optimization. This paper proposes a combined forecasting method through data preprocessing algorithm and artificial intelligence optimization. The combined prediction method first uses wavelet transform threshold processing to remove the noise data in the original data and then uses three separate methods to reduce noise. Forecast warehouse data and obtain intermediate forecast results. This article analyzes warehouse management and can solve the problems in the company’s warehouse management from the aspects of warehouse design and planning, warehouse design, and integrated warehouse management. After comparative analysis and selection, this paper uses the SLP method to rationally adjust and arrange the relative position and area of each functional area of the warehouse, and improve the evaluation index system. Experimental research shows that under the guidance of this article to optimize storage strategy, cargo location layout, and warehousing workflow, the employee reward mechanism mobilizes the enthusiasm of employees, improves work efficiency, and reduces storage costs. The above-mentioned various optimization and storage improvement measures finally reduced the total storage cost by 17%, effectively achieving the goal of cost control.

The Optimization of the Location of the Cargo in Three-Dimension Shelf: Employing the FP-Tree and the Artificial Fish Swarm Algorithms

The allocation issues of the location of the cargo have affected the operational efficiency of retail e-commerce warehouses tremendously. Adjusting the cargo location with the change of the order and the operation of the warehouse is a significant research area. A novel approach employing the FP-Tree and the Artificial Fish Swarm Algorithms is proposed. Firstly, energy consumption and shelf stability are employed for the location-allocation. Secondly, the association rules among product items are obtained by the FP-Tree Algorithm to mine frequent list of items. Furthermore, the frequency and the weight of product items are taken into account to ensure the local stability of the shelf during data mining. Thirdly, another method of the location-allocation is obtained with the objectives of the energy consumption and the overall shelf stability along with the frequent items stored nearby that is conducted by the Artificial Fish Swarm Algorithm. Finally, the picking order distance is obtained through two methods of the location-allocation above. The performance and efficiency of the novel introduced method have been confirmed by running the experiment. The outcomes of the simulation suggest that the introduced method has a higher performance concerning criterion called the picking order distance.

Optimizing the Cargo Location Assignment of Retail E-Commerce Based on an Artificial Fish Swarm Algorithm

An efficient storage strategy for retail e-commerce warehousing is important for minimizing the order retrieval time to improve the warehouse-output efficiency. In this paper, we consider a model and algorithm to solve the cargo location problem in a retail e-commerce warehouse. The problem is abstracted into storing cargo on three-dimensional shelves, and the mathematical model is built considering three objectives: efficiency, stability, and classification. An artificial swarm algorithm is designed to solve the proposed models. Computational experiments performed on a warehouse show that the proposed approach is effective at solving the cargo location assignment problem and is significant for the operation and organization of a retail e-commerce warehouse.

Research on Autonomous Vehicle Storage and Retrieval System Cargo Location Optimization in E-commerce Automated Warehouse

Cargo allocation optimization is important to improve the efficiency of e-commerce automated warehouse’s autonomous vehicle storage and retrieval system (AVS/RS) operations. Considering the electrical business logistics characteristic of small batch, batches, variety characteristics, this paper aiming at maximizing the highest efficiency and shelf stability for warehousing efficiency, we established an initial cargo location model, designed an adaptive multi-objective genetic algorithm. MATLAB software programming was used to implement the model solution, and an example verification was performed with an automation warehouse named Jing-dong in China. The comparison between the initial cargo location model and the random storage strategy shows that the model can significantly improve the overall warehousing efficiency and shelf stability of AVS/RS.

Integrated Optimization of Mixed Cargo Packing and Cargo Location Assignment in Automated Storage and Retrieval Systems

To improve the delivery efficiency of automated storage and retrieval system, the problem of the integrated optimization of mixed cargo packing and cargo location assignment is addressed. An integrated optimization model of mixed cargo packing and location assignments with the shortest time for the stacker in a certain historical period is established and is transformed into a conditional packing problem. An improved hybrid genetic algorithm based on a group coding method is designed to solve the problem. When the initial population is generated, a new heuristic algorithm is designed to improve the convergence speed of the genetic algorithm considering the correlation and frequency of the goods outbound. A heuristic algorithm for a two-dimensional rectangular-packing problem is designed to determine whether a variety of goods can be mixed in packing. Taking actual data from an automated storage and retrieval system for an aviation food company as an example, the established model and design algorithm are verified and the influence of changes in the outbound delivery orders on the optimization result is analyzed. The results show that compared to the method of separate storage of goods based on cube-per-order index rules and a phased optimization method of mixed storage of goods, an integrated optimization method of mixed cargo packing and location assignment can improve the outbound delivery efficiency of the stacking machine by 11.43–25.98% and 1.73–5.51%, respectively, and reduce the cargo location used by 50–55% and 0–10%, respectively. The stronger the correlation of the goods leaving a warehouse, the greater the potential of the design method in this paper to improve the efficiency of the stacker.

Cargo\u2013carrier interactions significantly contribute to micellar conformation and biodistribution

Strategies to deliver drugs using nanocarriers, which are passively or actively targeted to their alleged site of action might favorably affect benefit–risk profiles of novel therapeutics. Here we tested the hypothesis whether the physico-chemical properties of the cargo as well as the actual conditions during encapsulation interfere during formulation of nanoparticular cargo–carrier systems. On the basis of previous work, a versatile class of nanocarriers is polyether-based ABC triblock terpolymer micelles with diameters below 50 nm. Their tunable chemistry and size allows to systematically vary important parameters. We demonstrate in vivo differences in pharmacokinetics and biodistribution not only dependent on micellar net charge but also on the properties of encapsulated (model) drugs and their localization within the micelles. On the basis of in vitro and in vivo evidence we propose that depending on drug cargo and encapsulation conditions micelles with homogeneous or heterogeneous corona structure are formed, contributing to an altered pharmacokinetic profile as differences in cargo location occur. Thus, these interactions have to be considered when a carrier system is selected to achieve optimal delivery to a given tissue.

IMPROVING THE STABILITY TWO-LEVEL CAR HAULER

To improve the lateral stability of car hauler way you value optimal cargo location parameters, elastically mounted on a platform, developed a mathematical model of its motion. At the same time take into account fluctuations in cargo and car hauler. According to the simulation results revealed that the system for car «hauler – cargo» accounting for elastic properties leads to a significant decrease in the frequency and amplitude of the system vertical oscillations. Therefore, the presence of the cargo can be regarded as a dynamic passive damping (in the case of a correct choice and design of layout parameters). There is proposed to reduce the distance between the cargo and the upper platform by determination of maximum values of the cargo oscillations amplitudes. In turn, the reduction of the height of the platform reduces the height of the center of gravity of the system, improves the stability of car hauler.
 Keywords: car hauler, dynamic processes, fluctuations, platform, stability.

The impact of cargo monitoring systems usage on intermodal transport risk and costs

The research was carried out to verify the impact of using systems to monitor cargo location and parameters in the transportation chain. Three variants of cases were examined - a reference variant (without cargo monitoring systems), variant I (positioning systems), and variant II (monitoring cargo location and parameters). It was possible to assess the benefits of application of the monitoring systems of loading units in road transport. The transport chain was divided into separate processes. For each of them, the possible risk appearance was specified with percentage probability. On this basis, the simulation of transport cases was performed using Excel software. For the simulation results analysis, the statistical software 'MiniTab 17' and 'Statgraphic Centurion XVI' was used. Risk identification on each link of the supply chain allows taking actions in order to reduce costs, which is essential to the effective functioning of the company and increasing the level of customer service.

The impact of cargo monitoring systems usage on intermodal transport risk and costs

The research was carried out to verify the impact of using systems to monitor cargo location and parameters in the transportation chain. Three variants of cases were examined - a reference variant (without cargo monitoring systems), variant I (positioning systems), and variant II (monitoring cargo location and parameters). It was possible to assess the benefits of application of the monitoring systems of loading units in road transport. The transport chain was divided into separate processes. For each of them, the possible risk appearance was specified with percentage probability. On this basis, the simulation of transport cases was performed using Excel software. For the simulation results analysis, the statistical software 'MiniTab 17' and 'Statgraphic Centurion XVI' was used. Risk identification on each link of the supply chain allows taking actions in order to reduce costs, which is essential to the effective functioning of the company and increasing the level of customer service.

Location of Varying Hydrophobicity Zinc(II) Phthalocyanine-Type Photosensitizers in Methoxy Poly(ethylene oxide) and Poly(l-lactide) Block Copolymer Micelles Using 1H NMR and XPS Techniques.

Hydrophobic zinc(II) phthalocyanine-type derivatives, solubilized in polymeric micelles (PMs), provide a befitting group of so-called nanophotosensitizers, suitable for a variety of photodynamic therapy (PDT) protocols. The factors that influence the success of such products in PDT are the location of the active cargo in the PMs and the nanocarrier-enhanced ability to safely interact with biological systems and fulfill their therapeutic functions. Therefore, the aim of this work was to determine the solubilization loci of three phthalocyanines of varying hydrophobicity, i.e., zinc(II) phthalocyanine (ZnPc), along with its tetrasulfonic acid (ZnPc-sulfo4) and perfluorinated (ZnPcF16) derivatives, loaded in polymeric micelles of methoxy poly(ethylene oxide)-b-poly(l-lactide) (mPEG-b-PLLA), by means of 1H nuclear magnetic resonance (NMR) and X-ray photoelectron spectroscopy (XPS) combined with ion sputtering. Furthermore, the microenvironment influence upon the chemical and physical status of the solubilized cargo in PMs, expressed by photobleaching and reactive oxygen species (ROS) generation comparing to the same properties of native cargoes in solution, was also evaluated and discussed in regards to the probing location data. The studied phthalocyanine-loaded PMs exhibited good physical stability, high drug-loading efficiency, and a size of less than ca. 150 nm with low polydispersity indices. The formation of polymeric micelles and the solubilization locus were investigated by 1H NMR and XPS. ZnPc localized within the PM core, whereas both ZnPcF16 and ZnPc-sulfo4 - in the corona of PMs. We proved that the cargo locus is crucial for the photochemical properties of the studied phthalocyanines; the increase in photostability and ability to generate ROS in micellar solution compared to free photosensitizer was most significant for the photosensitizer in the PM core. Our results indicate the role of the cargo location in the PM microenvironment and demonstrate that such attempts are fundamental for improving the properties of photosensitizers and their assumed efficiency as nanophotosensitizers in PDT.