Routing Design Research Articles

A hybrid algorithm based on the proposed square strategy and NSGA-II for ship pipe route design

Ship pipe route design (SPRD) is a difficult and time-consuming job due to the complexity of the routing space and the large number of pipes. This paper introduces a hybrid optimization algorithm called SQNSGA-II based on the proposed Square strategy and NSGA-II to efficiently solve SPRD problems in complex situations. The details of the hybrid algorithm are introduced, including the principle of the Square strategy, genetic operators and pipe repair operators et al. Additionally, a new method called Intercept Search strategy is proposed for optimizing branch pipe design in complex scenarios. Finally, we conducted three cases of simulation experiments to demonstrate that the proposed algorithm and strategy can efficiently and accurately optimize the design of pipes, highlighting their pipe routing capabilities in complex engineering projects.

IoT-Driven solutions for VANET trustworthiness: Examining misconduct and position security challenges

Vehicular ad hoc networks (VANETs) improve the traffic management and road safety by exchanging real-time data between automobiles and roadside infrastructure. Reliable Intelligent Transport Systems (ITS) solutions tend to boost VANET data security, integrity and dependability. These systems communicate VANET data between infrastructure and automobiles using sensors, Internet of Things (IoT) devices and communication technologies. IoT-driven includes a Real-Time Traffic Observation optimizes VANET route design. Traffic management and safety improve with ITS-connected cars and infrastructure. Remote communication technologies enhance traffic management and decision-making by sending a real-time data between cars and infrastructure. Smart parking systems use real-time parking availability data from IoT sensors and devices to maximize space use and reduce congestion. Security and misbehavior are dependable problems in 40 IoT-driven VANET studies. Miscommunication and unstandardized are the main security issues which pose hazards. This review shows VANETs that requires authentication, encryption and anomaly detection to prevent attacks and IoT for transportation sector. This extensive review covers VANET reliability and IoT-driven real-time traffic monitoring, ITS, remote communication and intelligent parking systems. This review analyzes the metrics to assess the many detection techniques which includes, misconduct-Aware On-Demand Collaborative Intrusion Detection System (MACIDS) and Collision-Induced Dissociation Spectroscopy (CIDS), (i) Accuracy (ii) False Positive Rate, (iii) precision, (iv) recall (v) False Negative Rate and (vi) F1-Score in VANET security in Attack Detection Rates (ADR), misbehavior detection, evaluation metrics and detection algorithms were studied using CIC-IDS data. Due to misconduct and security issues, a strong IoT-driven solutions are required to improve VANET trustworthiness and offers a secure and reliable vehicular communication networks for safer and more efficient transportation systems.

Study on Spatiotemporal Behavior of Self-driving Tourists in Inner Mongolia

Against the backdrop of normalized tourism and upgraded consumption, self-driving tours have become one of the main choices for tourists. Faced with the booming self-driving tour market, it is of great significance to explore the spatial behavior characteristics and temporal constraint factors of self-driving tourists within a geographical range using GPS trajectory data. This exploration aids in the planning and design of self-driving tour routes, tourism products, and promotes the healthy and sustainable development of the self-driving tour industry. This paper selects Inner Mongolia Autonomous Region as the self-driving tour hotspot area, collects GPS data of self-driving tourists from 2017 to 2022 on the online platform "Foooooot" using Python, and conducts in-depth exploration and comparative analysis of the spatiotemporal behavior trajectories of self-driving tourists, aiming to explore the spatiotemporal behavior characteristics of self-driving tourists and their constraining factors.

Design of Tourist Routes in Scenic Spots -Taking Pan'an Lake Scenic Area as an Example

In this paper, we explore the application of 0-1 integer programming and mixed integer programming to solve the route design problem using the Pan'an Lake Scenic Area in Xuzhou as a case study. We aim to design scenic tour routes with the shortest walking distance and the longest visit time. We formulate the problem using a 0-1 integer programming model, with an objective function that minimizes the total route length. Constraints are established to ensure the route starts at Scenic Stone, ends at Wetland Commercial Street, each attraction is visited once, and there are no repeated paths. The research results of the article have certain reference significance for route optimization problems.

Design of emergency evacuation route for large buildings based on cloud computing and GIS big data

In order to ensure the safety of life and property in large buildings, the design of emergency evacuation routes for large buildings based on cloud computing and GIS big data is studied. Combining cloud computing and GIS big data, a command model for emergency evacuation of large buildings is built. Emergency evacuation functions are realized through the access layer, business logic layer, cloud computing layer and data layer. GIS big data of large buildings is stored in the model data layer. GIS geographic data is clustered through the MapReduce based parallel K-means clustering algorithm in the cloud computing layer. After clustering, the emergency evacuation road network of large buildings is constructed through GIS in the business logic layer. On the road network, the emergency evacuation route selection method combining Dikstra algorithm and ant colony algorithm is used to realize the optimal route selection of emergency evacuation of large buildings. Experiments show that this method can effectively select the best evacuation path in large buildings, and the evacuation speed of the selected path is fast, which can ensure the safety of people in buildings.

Optimizing Ecotourism in North Taihu Lake, Wuxi City, China: Integrating Back Propagation Neural Networks and Ant-Colony Algorithm for Sustainable Route Planning

Urbanization's rapid pace has sparked a growing interest in nature-focused travel experiences, highlighting the growing importance of ecotourism. This study presents an innovative algorithm for ecotourism route planning, focusing on aligning tourists with attractions to enhance growth and appeal. The research utilizes ecological attractions in the Taihu Lake scenic area as an experimental dataset, incorporating historical travel data to examine the relationship between user characteristics and ecotourism attractions. Backpropagation neural networks and one-hot encoding are employed to predict visitor experiences. At the same time, a new ecotourism route design method combining deep learning and an ant colony algorithm based on average distance is applied to formulate an optimal ecotourism route. Results indicate Yuan Tou Zhu and Ling Shan as the top recommended destinations, with the optimal path identified as 1, 2, 3, 6, 4, 5, 7. This suggests that considering individual tourist preferences significantly elevates visitor satisfaction in ecotourism route planning, and it reveals the positive impact of aligning tourist attributes with attraction features. The findings underscore the importance of integrating user preferences into ecotourism planning strategies. Prioritizing personalized tourist experiences significantly enhances the effectiveness of ecotourism route planning initiatives. The research contributes a comprehensive framework for revitalizing ecotourism in the digital age, recommending the prioritization of individual tourist inclinations and attraction compatibility. Furthermore, adopting deep learning techniques and one-hot encoding is suggested to enhance the accuracy and efficacy of ecotourism planning.

Integrated clustering and routing design and triangle path optimization for UAV-assisted wireless sensor networks

Integrated clustering and routing design and triangle path optimization for UAV-assisted wireless sensor networks

Integrated Host- and Content-Centric Routing for Efficient and Scalable Networking of UAV Swarm

Efficient and scalable networking is a key enabler of the Unmanned Aerial Vehicle (UAV) swarms, wherein multiple UAVs cooperatively execute complicated tasks. Despite the intermittent connections due to the UAV mobility, stable paths may exist temporally in periods like formation keeping, which is rarely considered or utilized in existing UAV routing designs. In this paper, we propose an integrated host- and content-centric routing (IHCR) mechanism to harness the advantages of both routing mechanisms. Specifically, the routing information of stable paths is reused in a host-centric manner to reduce the flooding for path exploring. In addition, the route failure detection and re-routing are content-centric to adjust to the topology dynamics. The challenges lie in the inherent contradiction between host-centric and content-centric routing mechanisms (e.g., naming spaces) and the tradeoff between path reusing and re-routing. To overcome these challenges, we appropriately incorporate node names into content names and then fully exploit reusable paths via time-based route failure detection and delayed forwarding. Packet-level simulation results show that IHCR increases the packet delivery ratio by 60.1%, and enlarges the achievable network scale by 4.2 times compared to state-of-the-art routing mechanisms.

Susceptibility of Legionella gormanii Membrane-Derived Phospholipids to the Peptide Action of Antimicrobial LL-37-Langmuir Monolayer Studies.

LL-37 is the only member of the cathelicidin-type host defense peptide family in humans. It exhibits broad-spectrum bactericidal activity, which represents a distinctive advantage for future therapeutic targets. The presence of choline in the growth medium for bacteria changes the composition and physicochemical properties of their membranes, which affects LL-37's activity as an antimicrobial agent. In this study, the effect of the LL-37 peptide on the phospholipid monolayers at the liquid-air interface imitating the membranes of Legionella gormanii bacteria was determined. The Langmuir monolayer technique was employed to prepare model membranes composed of individual classes of phospholipids-phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylglycerol (PG), cardiolipin (CL)-isolated from L. gormanii bacteria supplemented or non-supplemented with exogenous choline. Compression isotherms were obtained for the monolayers with or without the addition of the peptide to the subphase. Then, penetration tests were carried out for the phospholipid monolayers compressed to a surface pressure of 30 mN/m, followed by the insertion of the peptide into the subphase. Changes in the mean molecular area were observed over time. Our findings demonstrate the diversified effect of LL-37 on the phospholipid monolayers, depending on the bacteria growth conditions. The substantial changes in membrane properties due to its interactions with LL-37 enable us to propose a feasible mechanism of peptide action at a molecular level. This can be associated with the stable incorporation of the peptide inside the monolayer or with the disruption of the membrane leading to the removal (desorption) of molecules into the subphase. Understanding the role of antimicrobial peptides is crucial for the design and development of new strategies and routes for combating resistance to conventional antibiotics.

Auto-Routing Systems (ARSs) with 3D Piping for Sustainable Plant Projects Based on Artificial Intelligence (AI) and Digitalization of 2D Drawings and Specifications

The engineering sector is undergoing digital transformation (DT) alongside shifts in labor patterns. This study concentrates on piping design within plant engineering, aiming to develop a system for optimal piping route design using artificial intelligence (AI) technology. The objective is to overcome limitations related to time and costs in traditional manual piping design processes. The ultimate aim is to contribute to the digitalization of engineering processes and improve project performance. Initially, digital image processing was utilized to digitize piping and instrument diagram (P&ID) data and establish a line topology set (LTS). Subsequently, three-dimensional (3D) modeling digital tools were employed to create a user-friendly system environment that visually represents piping information. Dijkstra’s algorithm was implemented to determine the optimal piping route, considering various priorities during the design process. Finally, an interference avoidance algorithm was used to prevent clashes among piping, equipment, and structures. Hence, an auto-routing system (ARS), equipped with a logical algorithm and 3D environment for optimal piping design, was developed. To evaluate the effectiveness of the proposed model, a comparison was made between the bill of materials (BoM) from Company D’s chemical plant project and the BoM extracted from the ARS. The performance evaluation revealed that the accuracy in matching pipe weight and length was 105.7% and 84.9%, respectively. Additionally, the accuracy in matching the weight and quantity of fittings was found to be 99.7% and 83.9%, respectively. These findings indicate that current digitalized design technology does not ensure 100% accurate designs. Nevertheless, the results can still serve as a valuable reference for attaining optimal piping design. This study’s outcomes are anticipated to enhance work efficiency through DT in the engineering piping design sector and contribute to the sustainable growth of companies.

On the Joint Design of Microservice Deployment and Routing in Cloud Data Centers

On the Joint Design of Microservice Deployment and Routing in Cloud Data Centers

Optimization for Customized Bus Stop Planning, Order Schedule, and Routing Design in On-Demand Urban Mobility

Optimization for Customized Bus Stop Planning, Order Schedule, and Routing Design in On-Demand Urban Mobility

Does urban bus route assignment improve air quality?

Worldwide, one of the most important causes of mortality is air pollution. To solve this problem, governments have implemented policies to reduce on-road and industrial emissions. In this regard, the Barcelona city council and Transports Metropolitans de Barcelona (TMB) started implementing the Nova Xarxa de Bus (NXB) to redefine the bus network following the criteria of connectivity, efficiency, and rationality. This policy was implemented in seven phases from 2012 to 2018. In this context, this paper analyses the impact of this policy on Barcelona’s air quality using a dataset from 2008 to 2016. Using a difference-in-difference approach, we show that implementing these new routes increased air quality in Barcelona. Additionally, we show that pollution decreased in each phase analysed, especially in the air quality stations near the main roads. From our results, we can infer that an optimal bus route design can improve air quality in urban areas.

Design Optimization of a Soft Robotic Rehabilitation Glove Based on Finger Workspace Analysis.

The finger workspace is crucial for performing various grasping tasks. Thus, various soft rehabilitation gloves have been developed to assist individuals with paralyzed hands in activities of daily living (ADLs) or rehabilitation training. However, most soft robotic glove designs are insufficient to assist with various hand postures because most of them use an underactuated mechanism for design simplicity. Therefore, this paper presents a methodology for optimizing the design of a high-degree-of-freedom soft robotic glove while not increasing the design complexity. We defined the required functional workspace of the index finger based on ten frequently used grasping postures in ADLs. The design optimization was achieved by simulating the proposed finger-robot model to obtain a comparable workspace to the functional workspace. In particular, the moment arm length for extension was optimized to facilitate the grasping of large objects (precision disk and power sphere), whereas a torque-amplifying routing design was implemented to aid the grasping of small objects (lateral pinch and thumb-two-finger pinch). The effectiveness of the optimized design was validated through testing with a stroke survivor and comparing the assistive workspace. The observed workspace demonstrated that the optimized glove design could assist with nine out of the ten targeted grasping posture functional workspaces. Furthermore, the assessment of the grasping speed and force highlighted the glove's usability for various rehabilitation activities. We also present and discuss a generalized methodology to optimize the design parameters of a soft robotic glove that uses an underactuated mechanism to assist the targeted workspace. Overall, the proposed design optimization methodology serves as a tool for developing advanced hand rehabilitation robots, as it offers insight regarding the importance of routing optimization in terms of the workspace.

The elderly wayfinding performance in an informative healthcare design indoors

This study examines the influence of architectural design elements and age on the wayfinding performance (WP) of older adults in healthcare circulation patterns. The study was conducted at Milad Hospital in Tehran, Iran, and included the Emergency, Outpatient, Clinics, and Inpatient wards. The study used a quantitative research method to investigate and virtual reality (VR) to simulate. Wayfinders were shown the circulation patterns of five types of healthcare circulations in virtual reality (VR) using two design approaches: high indicative features (the most guiding design aids) and a neutral environment (the fewest design aids). The study revealed that architectural design elements and age influence users' WP. Initially, it is worth noting that the mental-perceptual conditions of users in both groups were almost indistinguishable. However, the records of the elderly group (from 66 to 82 years) indicated a lower frequency of environmental design aid scenes (base design), which enabled them to more effectively identify and focus on locating the destination points. Nevertheless, the control group, consisting of younger individuals (from 18 to 39 years), exhibited superior and more efficient performance than their senior counterparts. When the users of both groups perceived the route to be challenging to traverse, their performance dropped, and they felt disoriented and anxious. Also, the Corridor circulation pattern exhibited a relatively low level of navigational complexity. Overall, the results suggest that architects should prioritize the design of circulation routes that are easily recognizable and highlight prominent features while considering the cognitive and perceptual needs of the elderly population.

Electrokinetic Analyses Uncover the Rate‐Determining Step of Biomass‐Derived Monosaccharide Electroreduction on Copper

AbstractElectrochemical biomass conversion holds promise to upcycle carbon sources and produce valuable products while reducing greenhouse gas emissions. To this end, deep insight into the interfacial mechanism is essential for the rational design of an efficient electrocatalytic route, which is still an area of active research and development. Herein, we report the reduction of dihydroxyacetone (DHA)—the simplest monosaccharide derived from glycerol feedstock—to acetol, the vital chemical intermediate in industries, with faradaic efficiency of 85±5 % on a polycrystalline Cu electrode. DHA reduction follows preceding dehydration by coordination with the carbonyl and hydroxyl groups and the subsequent hydrogenation. The electrokinetic profile indicates that the rate‐determining step (RDS) includes a proton‐coupled electron transfer (PCET) to the dehydrated intermediate, revealed by coverage‐dependent Tafel slope and isotopic labeling experiments. An approximate zero‐order dependence of H+ suggests that water acts as the proton donor for the interfacial PCET process. Leveraging these insights, we formulate microkinetic models to illustrate its origin that Eley–Rideal (E−R) dominates over Langmuir–Hinshelwood (L−H) in governing Cu‐mediated DHA reduction, offering rational guidance that increasing the concentration of the adsorbed reactant alone would be sufficient to promote the activity in designing practical catalysts.

Route design in sheepdog system–traveling salesman problem formulation and evolutionary computation solution–

ABSTRACT In this study, we consider the guidance control problem of the sheepdog system, which involves the guidance of a flock using the characteristics of the sheepdog and sheep. Sheepdog systems require strategies to guide sheep agents to a goal area using small numbers of sheepdog agents, and various methods have been proposed. Previous studies have proposed a guidance control law to reliably guide sheep herds; however, the movement distance required by the sheepdog for guidance has not been considered. Therefore, in this study, we propose a novel guidance algorithm in which a supposedly efficient route for guiding a flock of sheep is designed via the traveling salesman problem and evolutionary computation. Numerical simulations were performed to confirm whether sheep flocks could be guided and controlled using the obtained guidance routes. We revealed that the proposed method reduces both the guidance failure rate and the guidance distance.

Electrokinetic Analyses Uncover the Rate-Determining Step of Biomass-Derived Monosaccharide Electroreduction on Copper.

Electrochemical biomass conversion holds promise to upcycle carbon sources and produce valuable products while reducing greenhouse gas emissions. To this end, deep insight into the interfacial mechanism is essential for the rational design of an efficient electrocatalytic route, which is still an area of active research and development. Herein, we report the reduction of dihydroxyacetone (DHA)-the simplest monosaccharide derived from glycerol feedstock-to acetol, the vital chemical intermediate in industries, with faradaic efficiency of 85±5 % on a polycrystalline Cu electrode. DHA reduction follows preceding dehydration by coordination with the carbonyl and hydroxyl groups and the subsequent hydrogenation. The electrokinetic profile indicates that the rate-determining step (RDS) includes a proton-coupled electron transfer (PCET) to the dehydrated intermediate, revealed by coverage-dependent Tafel slope and isotopic labeling experiments. An approximate zero-order dependence of H+ suggests that water acts as the proton donor for the interfacial PCET process. Leveraging these insights, we formulate microkinetic models to illustrate its origin that Eley-Rideal (E-R) dominates over Langmuir-Hinshelwood (L-H) in governing Cu-mediated DHA reduction, offering rational guidance that increasing the concentration of the adsorbed reactant alone would be sufficient to promote the activity in designing practical catalysts.

An artificial fish swarm optimization algorithm for the urban transit routing problem

The Urban Transit Routing Problem (UTRP) is an NP-hard discrete problem that deals with the design of routes for public transport systems. It is a highly complex, multiply constrained problem, while the evaluation of candidate route sets can prove both challenging and time-consuming, with many potential solutions rejected on the grounds of infeasibility. Due to its difficulty, metaheuristic methods, such us swarm intelligence algorithms, are considered highly suitable for the UTRP. The suitability of these methods heavily relies on the correct adaptation of the chosen method for a discrete-space problem, the initialization procedure, and the solution evaluation method. In this context, this study proposes an artificial fish swarm optimization algorithm for the efficient solution of the UTRP, presenting a novel discrete-space adaptation of the former. The results are subsequently compared to 14 other algorithms, including evolutionary, swarm intelligence and hyper-heuristic implementations, using Mandl’s widely used and accepted benchmark. Comparison of the produced solutions with published results on Mandl’s benchmark network, shows that the developed algorithm yields superior results to the existing techniques, yielding very high shares of direct trip coverage, which is vital for transit systems to attract riders and contribute to urban sustainability. A new indicator for operator cost calculation is also developed and integrated into our analysis, offering insights on the trade-offs between user and operator costs. Differences in generated solutions, influenced by the weighting factor value, can result in variations of up to 13% in direct trip coverage and 1.5 minutes in average travel time.

Automatic calibration of airborne LiDAR installation angle based on point cloud conjugate matching

Airborne LiDAR plays an important role in island detection, shallow ocean topography mapping and intertidal zone detection. The installation angle error usually leads to deviation between overlapping strips, which affects the accuracy of LiDAR point cloud data. However, previous methods had complex requirements for routes and calibration field, leading to inefficient calibration. This paper proposes an automatic installation angle error calibration algorithm based on point cloud conjugate matching, which does not require strict route design and field selection. In the algorithm, the conjugated point cloud is extracted by selecting routes and processing point cloud, and the installation angle error is calculated by matching the conjugate point cloud. Airborne LiDAR data from Shanghai Institute of Optics and Fine Mechanics is utilized to verify the method which show that the overlap degree of conjugate point clouds can reach 90% in different routes. This method is expected to dramatically improve the efficiency of system calibration and the convenience of measurement.