Optimization Design of the Multi-Layer Cross-Sectional Layout of An Umbilical Based on the GA-GLM

Marine umbilical is one of the key equipment for subsea oil and gas exploitation,which is usually integrated by a great number of different functional components with multi-layers.The layout of these components directly affects manufacturing,operation and storage performances of the umbilical.For the multi-layer cross-sectional layout design of the umbilical,a quantifiable multi-objective optimization model is established according to the operation and storage requirements.Considering the manufacturing factors,the multi-layering strategy based on contact point identification is introduced for a great number of functional components.Then,the GA-GLM global optimization algorithm is proposed combining the genetic algorithm and the generalized multiplier method,and the selection operator of the genetic algorithm is improved based on the steepest descent method.Genetic algorithm is used to find the optimal solution in the global space,which can converge from any initial layout to the feasible layout solution.The feasible layout solution is taken as the initial value of the generalized multiplier method for fast and accurate solution.Finally,taking umbilicals with a great number of components as examples,the results show that the cross-sectional performance of the umbilical obtained by optimization algorithm is better and the solution efficiency is higher.Meanwhile,the multi-layering strategy is effective and feasible.The design method proposed in this paper can quickly obtain the optimal multi-layer cross-sectional layout,which replaces the manual design,and provides useful reference and guidance for the umbilical industry.

Development of Fixture Layout Optimization for Thin-Walled Parts:A Review

An increasing number of researchers have researched fixture layout optimization for thin-walled part assembly during the past decades.However,few papers systematically review these researches.By analyzing existing literature,this paper summarizes the process of fixture layout optimization and the methods applied.The process of optimization is made up of optimization objective setting,assembly variation/deformation modeling,and fixture layout optimization.This paper makes a review of the fixture layout for thin-walled parts according to these three steps.First,two different kinds of optimization objectives are introduced.Researchers usually consider in-plane variations or out-of-plane deformations when designing objectives.Then,modeling methods for assembly variation and deformation are divided into two categories:Mechanism-based and data-based methods.Several common methods are discussed respectively.After that,optimization algorithms are reviewed systematically.There are two kinds of optimization algorithms:Traditional nonlinear programming and heuristic algorithms.Finally,discussions on the current situation are provided.The research direction of fixture layout optimization in the future is discussed from three aspects:Objective setting,improving modeling accuracy and optimization algorithms.Also,a new research point for fixture layout optimization is discussed.This paper systematically reviews the research on fixture layout optimization for thin-walled parts,and provides a reference for future research in this field.

Web Layout Design of Large Cavity Structures Based on Topology Optimization

Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas become a focal point for contemporary researchers. Therefore, this paper aims to investigate the topologyoptimization of large cavity structures as a means to enhance their performance, safety, and efficiency. By usingthe variable density method, lightweight design is achieved without compromising structural strength. Theoptimization model considers both concentrated and distributed loads, and utilizes techniques like sensitivityfiltering and projection to obtain a robust optimized configuration. The mechanical properties are checked bycomparing the stress distribution and displacement of the unoptimized and optimized structures under the sameload. The results confirm that the optimized structures exhibit improved mechanical properties, thus offering keyinsights for engineering lightweight, high-strength large cavity structures.

GNN Representation Learning and Multi-Objective Variable Neighborhood Search Algorithm for Wind Farm Layout Optimization

With the increasing demand for electrical services,wind farm layout optimization has been one of the biggest challenges that we have to deal with.Despite the promising performance of the heuristic algorithm on the route network design problem,the expressive capability and search performance of the algorithm on multi-objective problems remain unexplored.In this paper,the wind farm layout optimization problem is defined.Then,a multi-objective algorithm based on Graph Neural Network(GNN)and Variable Neighborhood Search(VNS)algorithm is proposed.GNN provides the basis representations for the following search algorithm so that the expressiveness and search accuracy of the algorithm can be improved.The multi-objective VNS algorithm is put forward by combining it with the multi-objective optimization algorithm to solve the problem with multiple objectives.The proposed algorithm is applied to the 18-node simulation example to evaluate the feasibility and practicality of the developed optimization strategy.The experiment on the simulation example shows that the proposed algorithm yields a reduction of 6.1% in Point of Common Coupling(PCC)over the current state-of-the-art algorithm,which means that the proposed algorithm designs a layout that improves the quality of the power supply by 6.1%at the same cost.The ablation experiments show that the proposed algorithm improves the power quality by more than 8.6% and 7.8% compared to both the original VNS algorithm and the multi-objective VNS algorithm.

Research on the Innovative Decisions of Supermarket Private Brands and Designated Manufacturers

One of the core competencies of a supermarket lies in its branding.With the continuous development of the market economy and the ongoing evolution of consumer demand,private brands have progressively emerged as significant contributors to supermarket growth.However,a pivotal developmental challenge for supermarkets is navigating the innovative decision-making process between private brands and designated manufacturers.This paper aims to investigate the innovative decisions between private brands and designated manufacturers,along with the relevant promotional strategies employed during entry into the United States market.

Optimizing Memory Access Efficiency in CUDA Kernel via Data Layout Technique

Over the past decade, Graphics Processing Units (GPUs) have revolutionized high-performance computing, playing pivotal roles in advancing fields like IoT, autonomous vehicles, and exascale computing. Despite these advancements, efficiently programming GPUs remains a daunting challenge, often relying on trial-and-error optimization methods. This paper introduces an optimization technique for CUDA programs through a novel Data Layout strategy, aimed at restructuring memory data arrangement to significantly enhance data access locality. Focusing on the dynamic programming algorithm for chained matrix multiplication—a critical operation across various domains including artificial intelligence (AI), high-performance computing (HPC), and the Internet of Things (IoT)—this technique facilitates more localized access. We specifically illustrate the importance of efficient matrix multiplication in these areas, underscoring the technique’s broader applicability and its potential to address some of the most pressing computational challenges in GPU-accelerated applications. Our findings reveal a remarkable reduction in memory consumption and a substantial 50% decrease in execution time for CUDA programs utilizing this technique, thereby setting a new benchmark for optimization in GPU computing.

Optimizing wind farm layout for enhanced electricity extraction using a new hybrid PSO-ANN method

With the growing need for renewable energy,wind farms are playing an important role in generating clean power from wind resources.The best wind turbine architecture in a wind farm has a major influence on the energy extraction efficiency.This paper describes a unique strategy for optimizing wind turbine locations on a wind farm that combines the capabilities of particle swarm optimization(PSO)and artificial neural networks(ANNs).The PSO method was used to explore the solution space and develop preliminary turbine layouts,and the ANN model was used to fine-tune the placements based on the predicted energy generation.The proposed hybrid technique seeks to increase energy output while considering site-specific wind patterns and topographical limits.The efficacy and superiority of the hybrid PSO-ANN methodology are proved through comprehensive simulations and comparisons with existing approaches,giving exciting prospects for developing more efficient and sustainable wind farms.The integration of ANNs and PSO in our methodology is of paramount importance because it leverages the complementary strengths of both techniques.Furthermore,this novel methodology harnesses historical data through ANNs to identify optimal turbine positions that align with the wind speed and direction and enhance energy extraction efficiency.A notable increase in power generation is observed across various scenarios.The percentage increase in the power generation ranged from approximately 7.7%to 11.1%.Owing to its versatility and adaptability to site-specific conditions,the hybrid model offers promising prospects for advancing the field of wind farm layout optimization and contributing to a greener and more sustainable energy future.

Semantic Document Layout Analysis of Handwritten Manuscripts

A document layout can be more informative than merely a document’s visual and structural appearance.Thus,document layout analysis(DLA)is considered a necessary prerequisite for advanced processing and detailed document image analysis to be further used in several applications and different objectives.This research extends the traditional approaches of DLA and introduces the concept of semantic document layout analysis(SDLA)by proposing a novel framework for semantic layout analysis and characterization of handwritten manuscripts.The proposed SDLA approach enables the derivation of implicit information and semantic characteristics,which can be effectively utilized in dozens of practical applications for various purposes,in a way bridging the semantic gap and providingmore understandable high-level document image analysis and more invariant characterization via absolute and relative labeling.This approach is validated and evaluated on a large dataset ofArabic handwrittenmanuscripts comprising complex layouts.The experimental work shows promising results in terms of accurate and effective semantic characteristic-based clustering and retrieval of handwritten manuscripts.It also indicates the expected efficacy of using the capabilities of the proposed approach in automating and facilitating many functional,reallife tasks such as effort estimation and pricing of transcription or typing of such complex manuscripts.

Application of a Parallel Adaptive Cuckoo Search Algorithm in the Rectangle Layout Problem

The meta-heuristic algorithm is a global probabilistic search algorithm for the iterative solution.It has good performance in global optimization fields such as maximization.In this paper,a new adaptive parameter strategy and a parallel communication strategy are proposed to further improve the Cuckoo Search(CS)algorithm.This strategy greatly improves the convergence speed and accuracy of the algorithm and strengthens the algorithm’s ability to jump out of the local optimal.This paper compares the optimization performance of Parallel Adaptive Cuckoo Search(PACS)with CS,Parallel Cuckoo Search(PCS),Particle Swarm Optimization(PSO),Sine Cosine Algorithm(SCA),Grey Wolf Optimizer(GWO),Whale Optimization Algorithm(WOA),Differential Evolution(DE)and Artificial Bee Colony(ABC)algorithms by using the CEC-2013 test function.The results show that PACS algorithmoutperforms other algorithms in 20 of 28 test functions.Due to the superior performance of PACS algorithm,this paper uses it to solve the problem of the rectangular layout.Experimental results show that this scheme has a significant effect,and the material utilization rate is improved from89.5%to 97.8%after optimization.

A Chaotic Local Search-Based Particle Swarm Optimizer for Large-Scale Complex Wind Farm Layout Optimization

Wind energy has been widely applied in power generation to alleviate climate problems.The wind turbine layout of a wind farm is a primary factor of impacting power conversion efficiency due to the wake effect that reduces the power outputs of wind turbines located in downstream.Wind farm layout optimization(WFLO)aims to reduce the wake effect for maximizing the power outputs of the wind farm.Nevertheless,the wake effect among wind turbines increases significantly as the number of wind turbines increases in the wind farm,which severely affect power conversion efficiency.Conventional heuristic algorithms suffer from issues of low solution quality and local optimum for large-scale WFLO under complex wind scenarios.Thus,a chaotic local search-based genetic learning particle swarm optimizer(CGPSO)is proposed to optimize large-scale WFLO problems.CGPSO is tested on four larger-scale wind farms under four complex wind scenarios and compares with eight state-of-the-art algorithms.The experiment results indicate that CGPSO significantly outperforms its competitors in terms of performance,stability,and robustness.To be specific,a success and failure memories-based selection is proposed to choose a chaotic map for chaotic search local.It improves the solution quality.The parameter and search pattern of chaotic local search are also analyzed for WFLO problems.

Prevalence and Antimicrobial Susceptibility Status of Gram-Negative and Gram-Positive Bacteria on Handheld Shopping Trolleys and Baskets in Supermarkets in Ndola, Zambia

Background: Supermarkets are a place visited by individuals with different health conditions daily where microbiological contaminants through touch onto fomites such as trolleys and baskets can be passed on to other people hence potentially spreading infectious diseases. This study aimed to investigate the presence of Gram-negative and Gram-positive bacteria on handheld shopping trolleys and baskets and their antimicrobial susceptibility status against commonly used antibiotics in Zambia. Methods: A cross-sectional study was conducted. Trolleys and basket handles were swabbed and standard microbiological methods were used to identify the bacteria and disc diffusion to determine their antimicrobial susceptibility status. Data was collected from December 2021 to April 2022. Data was analysed using IBM Statistical Package for Social Sciences (SPSS) Version 22. Results: Twenty-eight percent of the 200 total samples were found to be culture-positive and predominant isolates were Staphylococcus aureus (17.3%), Pseudomonas species (4.5%), Escherichia coli (2%), Corynebacterium species (2%), Staphylococcus species (1.5%) and Enterobacter aerogenes (0.5%). Staphylococcus aureus showed the most resistance to azithromycin (17%) followed by ciprofloxacin (2.8%), nitrofurantoin (2.8%) and chloramphenicol (2.8%). Escherichia coli showed 100% resistance to amoxicillin, cloxacillin and ampicillin, 75% resistance to ciprofloxacin and the least resistance to azithromycin (25%) while it was susceptible to nitrofurantoin. Staphylococcus species, Corynebacterium species, Enterobacter aerogenes and Pseudomonas species showed no resistance to any antibiotics. Conclusion: The study showed the presence of microorganisms with considerable antimicrobial resistance to antibiotics in Zambia on trolley and basket handles indicating the need for more initiatives to address proper hygiene in public environmental sites for better infection prevention and control.

Advanced surface coil layout with intrinsic noise cancellation properties for surface-NMR applications

A recent study demonstrated that in small-scale prepolarized surface nuclear magnetic resonance(SNMR-PP)measurements with a footprint of a few square meters,customized PP switch-off ramps can serve as an efficient excitation mechanism,eliminating the requirement for a conventional oscillating excitation pulse.This approach enables the detection of short relaxation signals from the unsaturated soil zone and can,therefore,be used to directly provide soil moisture and pore geometry information.Because ultimately such small-scale SNMR-PP setups are intended for a mobile application,it is necessary to develop strategies that allow for speedy measurement progress and do not require noise cancellation protocols based on reference stations.Hence,we developed a new concentric figure-of-eight(cFOE)loop layout that combines the direction independence of a circular loop with the intrinsic noise cancellation properties of a classical FOE-loop.This approach significantly decreases the measurement time because suitable signal-to-noise ratios are reached much faster compared to a classical circular loop and will bring us one step further toward fast and non-invasive soil moisture mapping applications.

Commodity layout in supermarkets:using the integration of the comprehensive related value method and genetic algorithm

The existing shelf layout methods do not explicitly consider the attention and relevancy of the commodity systematically and thus have failed to capture the invalid associations,resulting in poor sales impact and customer satisfaction.For such shortcomings,in this paper,we propose a mathematical programming approach for shelf layout problems based on comprehensive related value.First,we introduce the concepts of related value considering both attention and relevancy;second,we give the concept of adjacent utility value and the freedom of placement,and further analyze the impact of the same commodity on surrounding commodities due to different placement positions;third,we establish a new comprehensive related value-based commodity layout optimization model(CRV-CL)and provide the solution steps integrating with a genetic algorithm.Finally,we analyze the characteristics of CRV-CL through a specific case.The simulation results indicate the overall relevancy after applying the CRV-CL model.

A Spacecra Equipment Layout Optimization Method for Diverse and Competitive Design

The spacecraequipment layout optimization design(SELOD)problems with complicated performance con-straints and diversity are studied in this paper.The previous literature uses the gradient-based algorithm to obtain optimized non-overlap layout schemes from randomly initialized cases eectively.However,these local optimal solutions are too dicult to jump out of their current relative geometry relationships,signi􀀀cantly limiting their further improvement in performance indicators.Therefore,considering the geometric diversity of layout schemes is put forward to alleviate this limitation.First,similarity measures,including modi􀀀ed cosine similarity and gaussian kernel function similarity,are introduced into the layout optimization process.Then the optimization produces a set of feasible layout candidates with the most remarkable dierence in geometric distribution and the most representative schemes are sampled.Finally,these feasible geometric solutions are used as initial solutions to optimize the physical performance indicators of the spacecra,and diversi􀀀ed layout schemes of spacecraequipment are generated for the engineering practice.The validity and eectiveness of the proposed methodology are demonstrated by two SELOD applications.

Study on the general layout of semi-submersible offshore drilling platforms based on process flow

The general layout of 6th generation semi-submersible drilling platforms is the main factor impacting the efficiency of their drilling operations. This paper provides a compound/integrated algorithm based on process flow that is aimed at improving efficiency, while giving attention to stability and safety at the same time. The paper describes the process flow of dual drilling centers and a hierarchical division of rigs based on the different modes of transportation of various drilling support systems. The general layout-centripetal overall arrangement spatially was determined based on drilling efficiency. We derived our modules according to drilling functionality; the modules became our basic layout units. We applied different layout algorithm to mark out the upper and lower decks. That is, the upper deck was designed based on the lowest transportation cost while the lower deck＇s calculations were based on the best-fit scope. Storage configurations in columns and pontoons were also considered for the layout design. Finally the center of gravity was taken into consideration and the general layout was adjusted accordingly, to result in an optimal center of gravity. The methodology of the general layout can provide a reference for implementation of domestic designs of semi-submersible rigs.

NOVEL APPROACH TO LOCATOR LAYOUT OPTIMIZATION BASED ON GENETIC ALGORITHM

Proper fixture design is crucial to obtain the better product quality according to the design specification during the workpiece fabrication. Locator layout planning is one of the most important tasks in the fixture design process. However, the design of a fixture relies heavily on the designerts expertise and experience up to now. Therefore, a new approach to loeator layout determination for workpieces with arbitrary complex surfaces is pro- posed for the first time. Firstly, based on the fuzzy judgment method, the proper locating reference and locator - numbers are determined with consideration of surface type, surface area and position tolerance. Secondly, the lo- cator positions are optimized by genetic algorithm（GA）. Finally, a typical example shows that the approach is su- perior to the experiential method and can improve positioning accuracy effectively.

The Evolution of Landscape Layout Concept of Lingnan Taoist Zuting Temples in the Qing Dynasty

The replacement of Lingnan Taoist Zuting Temples from Lingbao Sect to Quanzhen Sect in the Qing Dynasty has led to the change of the layout of Taoist temples on Luofu Mountain. Through literature review, field research, image comparison and other research methods, the paper explores how the layout of the Taoist temples on Luofu Mountain evolved from the Four Taoist Temples in the Gehong period to the Five Taoist Temples in the Qing Dynasty under the influence of different Taoist ideologies, aiming to explore the cultural implications of the evolution of the layout of Lingnan Taoism Zuting Temple in the Qing Dynasty.

Redesign Facility Layout with a Kaizen Approach in Testing Laboratory at Balai Pengujian&Sertifikat Mutu Barang Makassar

In trading activities,especially exports in the food commodities sector,several documents must be made and completed by exporters,such as Certificate of Quality,Test-Certificate,and Chemical Analysis.Balai Pengujian&Sertifikasi Mutu Barang Makassar is a government agency operating in South Celebes that tests the quality of various agricultural and plantation commodities.From year to year,demand for testing services has increased along with the number of exports.So,testing activities have changed in terms of facility layout requirements resulting in overwhelmed in carrying out the testing process.Test rooms are not connected based on the current testing flow causing the tester’s ineffective work patterns.This study aims to redesign the layout of the facilities in the testing laboratory with the Kaizen approach to support the smooth testing process.The results of this study indicate that the proposed floor area uses a 150% allowance so the calculation requires a floor area of 42.52 m^(2).After that,an analysis of the proximity of the facilities is carried out by making ARC(Activity Relationship Chart)and ARD(Activity Relationship Diagram).Based on ARD,a template is made for the layout of testing laboratory facilities.This study applies Kaizen theory with the 5S concept to obtain a neater design,namely Seiri and Seiton in the refreshment laboratory and weighing room,Seiso on testing equipment in all testing laboratory rooms,Seiketsu and Shitsuke applied to all rooms in the testing laboratory.

Cellular manufacturing layout on adding/removing machines

In order to rapidly respond to the complex and mutational market, a new facility layout plan based on cellular manufacturing is proposed, which gives consideration to high efficiency and flexibility. The plan designs two phases of integrated cell layout, i.e., cell construction and cell system layout, on the condition of adding/removing machines. First, in view of the costs of logics and machine-relocation, the cell construction based on the alternative processing routes and intra-cell layout are integrated as a whole, which achieves cell formation, process planning and the intra-cell layout in a single step. Secondly, an approach of a continuous optimized multi-line layout for solving the cell system layout problem is proposed, which eliminates the coupling relationship from the machine-relocation and realizes an integrated design of the two phases of the cell layout. An application based on real factory data is optimally solved by the Matlab 7.0 software to validate and verify the models.

HSCA-Net: A Hybrid Spatial-Channel Attention Network in Multiscale Feature Pyramid for Document Layout Analysis

Document images often contain various page components and complex logical structures,which make document layout analysis task challenging.For most deep learning-based document layout analysis methods,convolutional neural networks(CNNs)are adopted as the feature extraction networks.In this paper,a hybrid spatial-channel attention network(HSCA-Net)is proposed to improve feature extraction capability by introducing attention mechanism to explore more salient properties within document pages.The HSCA-Net consists of spatial attention module(SAM),channel attention module(CAM),and designed lateral attention connection.CAM adaptively adjusts channel feature responses by emphasizing selective information,which depends on the contribution of the features of each channel.SAM guides CNNs to focus on the informative contents and capture global context information among page objects.The lateral attention connection incorporates SAM and CAM into multiscale feature pyramid network,and thus retains original feature information.The effectiveness and adaptability of HSCA-Net are evaluated through multiple experiments on publicly available datasets such as PubLayNet,ICDAR-POD,and Article Regions.Experimental results demonstrate that HSCA-Net achieves state-of-the-art performance on document layout analysis task.