Service Routing Research Articles

Analysis Service Process of Aircraft Turnaround Operations by Petri Net

Airport collaborative decision-making has put forward higher requirements for aircraft turnaround operations. In order to improve the efficiency of aircraft turnaround operations, this paper improves the Petri net model based on the characteristics of MATLAB language. It gives the specific steps to analyze the influence of aircraft turnaround operations period on the apron flight viable service route. The experimental analysis shows that the change in passenger cabin cleaning, catering, and air bridge disconnecting within the routine service time does not affect the number of viable service routes and critical operations of aircraft turnaround service. Suppose the time of four operations, the bridge connecting, water clearing, passenger deboarding, and water filling, are respectively set in the interval [1.43, 1.98], [8, 8.7], [10.5, 11] and [8.1, 9.9], the number of viable service routes will only achieve two values. In that case, the bigger one is 4.7543 * 1076 with the 72% generating probability. The other is 3.5715 * 1076, which is 3.11 * 104 times as many as the minimum value obtained by the regular value interval of four operations, improving the quality of the minimum number of viable service routes. The results indicate that setting the time of some aircraft turnaround operations within a reasonable range will improve the number of viable service routes.

Collaborative stochastic expansion planning of cyber‐physical system considering extreme scenarios

AbstractIn this paper, a collaborative stochastic expansion planning model of cyber‐physical system (CPS) with resilience constraints is proposed. The model can reduce the coupling risk and enhance the resilience under extreme scenarios, from the perspective of the structural/functional coupling between the physical and cyber systems. The model is to collaboratively optimize expansion transmission line siting, expansion communication fibre siting, and service routing distribution to minimize total investment cost. Constraints are divided into conventional constraints and resilience constraints. In the resilience constraints, the impact of cyber failures on the dispatch strategy is analyzed, and the load shedding in stochastic scenarios is limited to guarantee the resilience of the planning scheme. Particularly, to reach a stable solution for the stochastic planning, a mixed scenario set is proposed based on the probabilistic typhoon model and the complex network theory. Finally, the model is solved by the progressive hedging (PH) algorithm. The case studies of the IEEE RTS‐79 test system demonstrate that, compared with the traditional independent planning model, the model proposed in this paper performs better in limiting load loss and enhancing resilience under extreme scenarios.

Quantifying bus route service disruptions under interdependent cascading failures of a multimodal public transit system based on an improved coupled map lattice model

The coupled map lattice (CML) model can present rich spatiotemporal dynamic behaviors of complex systems, e.g., it has been observed to have good adaptability in the cascading failure modeling of subway networks (SNs). However, most studies rarely considered an interdependency between an SN and a bus network (BN), which reveals an open problem concerning the CML model's adaptability to a multimodal public transit system (MPTS). This paper develops an improved CML model to simulate interdependent cascading failures of an MPTS and quantify bus route service disruptions for amplifying severe consequences of failures. Remarkably, an interdependency integrating operational and nonlinear geographical interdependencies is proposed to modify the node state evolutionary function and model cascading failures across layers. Moreover, an estimation method for the node initial state is proposed to accommodate the initial value-sensitive dependence due to a logistic chaotic map involved in the evolutionary function. Finally, a case is simulated to verify the model's adaptability and enlighten operation management. Results indicate that (i) the neglect of interdependency causes an overestimation of the severity of cascading failures of an SN while a severe underestimation of those of a BN; (ii) the management and engineering measures to adjust transfers both have a phase transition point on the controllability of cascading failures, and the latter exhibits more a direct and comprehensive effect.

Service Routing in Multi-Tier Edge Computing: A Matching Game Approach

Although microservice envisioned as a promising approach for edge applications which can improves the development efficiency and the deployment productivity, it also leads to the operational complexity during service runtime. This leads to the emergence of service mesh, a decided infrastructure layer over microservices for reliable service-to-service communication. However, when migrating the service mesh to the multi-tier edge computing, the corresponding extensions on the top of service mesh is needed to overcome the challenges brought by the multi-tier edge servers, shared microservices and diverse QoS requirements. Therefore, in this paper, we investigate the problem of service routing to achieve the efficient microservice-based service provision in multi-tier edge computing. The objective is to route user requests to the optimal microservice instances with low service delay and resource cost. To this end, we first formulate the service routing problem as an integer non-linear optimization problem, which is NP-hard. Then we map it to a many-to-one matching problem by employing the matching game theory and propose a dependency-aware deferred acceptance algorithm with dynamic quota. The experimental results based on a real-world dataset demonstrate that our proposed algorithm can significantly outperform existing representative algorithms in terms of service delay and resource cost.

Conceptual Framework for Dynamic Optimal Airspace Configuration for Urban Air Mobility

In this work, a framework for optimizing the configuration of service areas in airspace into disparate partitions is demonstrated in the context of urban air mobility (UAM) operations. This framework is applied to a conceptual UAM airspace configuration, where a free-flight-based routing service and a corridor-based routing service are dynamically allocated to control different portions of the airspace over time, based on traffic demand. This allocation seeks to determine the least amount of structured coordination (in terms of active flight corridors) needed to safely meet traffic demand. This framework integrates several modeling components, including a novel spatiotemporal graph theoretic UAM traffic model capable of optimizing vehicle trajectories while maintaining multiple flight constraints. Airspace complexity and trajectory efficiency metrics are both implemented to quantify the overall safety and cumulative cost of routing a set of missions according to a given airspace configuration. Finally, spatial airspace partitions are managed using a support vector machine-based algorithm. Metrics are then applied to optimize the airspace configurations, according to desired objectives. Simulated results show that this framework can produce airspace configurations that ensure safety, while providing trajectory efficiency more effectively than purely uniform free-flight or corridor-based flight. This is demonstrated for both low- and high-density traffic scenarios.

Evaluating Public and Private Transport of Lahore

The growth of urbanization, as a result, has led to a higher number of motor vehicles, due to which there has been a considerable increase in traffic volumes in recent years. The existing road capacity and service levels do not fully meet the current needs of commuter traffic and transport. Along with providing fixed route services, transit systems integrated with these services have become a necessity for the community. The research design includes selecting a case study area, Lahore. The means of systemization that have been adopted to achieve the objectives of the research carried out include topic selection, comprehensive literature review in the context of local and international scenarios, data collection covering primary and secondary, data analysis using Excel and SPSS software, interpretation of data and placement of appropriate proposals. The main result of this study is that by improving public transport safety and public transport management, people's preference for using public transport will increase. Also, public transport's cleanliness and service level will increase; hence, the preference for using public transport will increase. The research's recommended solution for the city of Lahore has been designed locally to meet the majority problem, as the solution must be low-cost, environmentally sustainable, and responsive to the social demands of the local community.

A Low-Cost Sensor System Installed in Buses to Monitor Air Quality in Cities

Air pollution is an important source of morbidity and mortality. It is essential to understand to what levels of air pollution citizens are exposed, especially in urban areas. Low-cost sensors are an easy-to-use option to obtain real-time air quality (AQ) data, provided that they go through specific quality control procedures. This paper evaluates the reliability of the ExpoLIS system. This system is composed of sensor nodes installed in buses, and a Health Optimal Routing Service App to inform the commuters about their exposure, dose, and the transport's emissions. A sensor node, including a particulate matter (PM) sensor (Alphasense OPC-N3), was evaluated in laboratory conditions and at an AQ monitoring station. In laboratory conditions (approximately constant temperature and humidity conditions), the PM sensor obtained excellent correlations (R2≈1) against the reference equipment. At the monitoring station, the OPC-N3 showed considerable data dispersion. After several corrections based on the k-Köhler theory and Multiple Regression Analysis, the deviation was reduced and the correlation with the reference improved. Finally, the ExpoLIS system was installed, leading to the production of AQ maps with high spatial and temporal resolution, and to the demonstration of the Health Optimal Routing Service App as a valuable tool.

A Reinforcement Learning approach for bus network design and frequency setting optimisation

This paper proposes a new approach to solve the problem of bus network design and frequency setting (BNDFS). Transit network design must satisfy the needs of both service users and transit operators. Numerous optimisation techniques have been proposed for BNDFS in the literature. Previous approaches tend to adopt a sequential optimisation strategy that conducts network routing and service frequency setting in two separate steps. To address the limitation of sequential optimisation, our new algorithm uses Reinforcement Learning for a simultaneous optimisation of three key components of BNDFS: the number of bus routes, the route design and service frequencies. The algorithm can design the best set of bus routes without defining the total number of bus routes in advance, which can reduce the overall computational time. The proposed algorithm was tested on the benchmark Mandl Swiss network. The algorithm is further extended to the routing of express services. The validation includes additional test scenarios which modify the transit demand level on the Mandl network. The new algorithm can be useful to assist transit agencies and planners in improving existing routing and service frequency to cope with changing demand conditions.

Integrated Planning of Park-and-Ride Facilities and BRT-Based Public Transport Services (Case Study of Campus Parking Optimization at Udayana University in Denpasar City)

One aspect that has not been considered in the process of transforming public transportation or angkutan umum (AU) in the Metropolitan Sarbagita area of Bali is integration, specifically physical integration (integration with walking, biking, and park-andride). We propose a framework for integrated parking planning at the University of Udayana (UNUD) campus in the city of Denpasar as an informal park-and-ride (PR) integrated with existing AU, specifically the Trans Sarbagita corridor 2 (City-GWK) which passes through the Denpasar and Bukit campuses in the Badung district. Integrated public transportation services are an attractive new form of service that combines fixed route services with responsive on-demand services. The goal of this study is to identify users of the PR at the UNUD campus and investigate their motives, demand, and preferences towards this option. In this paper, a comprehensive background is provided to describe the issues and challenges related to AU operations, directing research into the area of untapped issues by specifically discussing all the steps that must be taken when implementing an integrated approach at the operational and policy level towards sustainable mobility, transportation equity, and door-to-door services.

Municipal Solid Waste Collection: Challenges, Strategies and Perspectives in the Optimization of a Municipal Route in a Southern Mexican Town

Solid waste management represents a challenge for municipalities, particularly at the collection stage. The high costs involved in its operation make it difficult to provide the service in all its communities, which results in bad practices (burning, burying, or dumping into a river) and the proliferation of open dumps. Collection efficiency is aggravated by poor route planning, narrow road networks, and irregular scheduling. This research proposes and develops the following objectives: (1) an analysis of the technical and logistical conditions of a town, (2) an improved municipal route for waste collection, and (3) the practical implications identified in the optimization of the service (challenges, strategies, and perspectives). During the study period (2018, 2019 and 2021), the following steps were carried out: (1) field trips to monitor the formal and informal routes, georeferencing each stop with a global positioning system, (2) semi-structured interviews to route personnel to learn about technical and logistical aspects, (3) the downloading of cartographic data for digitization, and (4) a network analysis aimed at designing an optimal route for formal collection and the spatial scope of the informal routes. The current technical and logistical analysis detected inefficiency in collection due to weak municipal operational planning and the irregular frequency of visits to the locality. The locality produces an average of 2.8 tons per day and its largest volume is organic waste (68.3%), followed by non-recyclable inorganic waste (21.2%), and recyclable waste (10.5%). In terms of results for the optimization of the municipal collection route, it is estimated that there will be an improvement in the time of the day of approximately 2 h less, going through 95 points when its schedule is 60 collection points, while the distance factor does not suffer changes due to the fact that there are no alternate routes between the departure and destination route. Among the main challenges faced by the municipalities are the limited budgets for basic sanitation services, which is why technological strategies and trained human resources are required for better municipal solid waste management. From a technical perspective, geographic information systems are a current trend to model and optimize service routes, with which a better scenario can be proposed. From a social perspective, community participation works as a key factor to carry out activities focused on finding solutions to the problems related to municipal solid waste management.

Efficient Clustering Using Memetic Adaptive Hill Climbing Algorithm in WSN

Wireless Sensor Networks are composed of autonomous sensing devices which are interconnected to form a closed network. This closed network is intended to share sensitive location-centric information from a source node to the base station through efficient routing mechanisms. The efficiency of the sensor node is energy bounded, acts as a concentrated area for most researchers to offer a solution for the early draining power of sensors. Network management plays a significant role in wireless sensor networks, which was obsessed with the factors like the reliability of the network, resource management, energy-efficient routing, and scalability of services. The topology of the wireless sensor networks acts driven factor for network efficiency which can be effectively maintained by performing the clustering process effectively. More solutions and clustering algorithms have been offered by various researchers, but the concern of reduced efficiency in the routing process and network management still exists. This research paper offers a hybrid algorithm composed of a memetic algorithm which is an enhanced version of a genetic algorithm integrated with the adaptive hill-climbing algorithm for performing energy-efficient clustering process in the wireless sensor networks. The memetic algorithm employs a local searching methodology to mitigate the premature convergence, while the adaptive hill-climbing algorithm is a local search algorithm that persistently migrates towards the increased elevation to determine the peak of the mountain (i.e.,) best cluster head in the wireless sensor networks. The proposed hybrid algorithm is compared with the state of art clustering algorithm to prove that the proposed algorithm outperforms in terms of a network life-time, energy consumption, throughput, etc.

Evaluating Public and Private Transport of Lahore

Increase in population is a dominant problem that is taking place throughout the whole world and its main cause is rapid urbanizations. Urbanized growth, consequently, has led to a higher number of motorized vehicles, because of which there has been a considerable increase in the number of traffic volume in the recent years. The existing road capacity and level of service does not fully cater the present traffic and transportation needs of commuters. Urban transportation concerns are hampering the growth of sustainable transportation system across the country. Along with the provision of fixed route service, an integrated transit system with this service is the need of a community. The design of the research includes the selection of case study area that is Lahore. The systemized means that has been adopted for accomplishing the objectives of the study conducted include topic selection, comprehensive literature review in context of local along with international scenario, data collection which includes both primary and secondary, data analysis using Excel and SPSS software, data interpretation and laying down suitable proposals. Report writing is being carried out side by side with all other tasks. The major outcomes of the study is by improving the security of public transport and management of public transport the preference of people to use public transport will increases. Also the cleanliness and level of service of public transport will improve then the preference to use public transport will increase. The solution that research recommended for Lahore city is one that has been locally designed to meet the majority's problems, as the solution should be low-cost, environmentally sustainable, and responsive to the social demands of the local people.

A Review of the Vehicle Routing Problem and the Current Routing Services in Smart Cities

In this survey, the issues of urban routing are analyzed, and critical considerations for smart and cost-effective delivery services are highlighted. Smart cities require intelligent services and solutions to address their routing issues. This article gives a brief description of current services that either apply classical methods or services that employ machine learning approaches. Furthermore, a comparison of the most promising research options in regard to VRP is provided. Finally, an initial design of a holistic scheme that would optimally combine several tools and approaches to serve the needs of different users with regard to the VRP is presented.

Cluster Analysis Of Marine Toll Service Area To Minimize Price Disparity To Inprove The Economy Of The East Indonesian Region In The Era Of The Covid-19 Pandemic

High price disparity is an economic problem that causes the welfare level of the population to be low. The government through the Sea Highway program tries to reduce price disparities through subsidized and scheduled sea transportation to serve several ports in Indonesia, one of which is in the province of Riau Islands. The Strait of Lampa Port is one of the marine transportation nodes which is a stopover point for Sea Toll boats on the T-3 route serving Natuna Regency. This port has the status of a regional feeder port with the hinterland area of Natuna Regency with Ranai as the district capital. This study aims to provide input related to the clustering of the Marine Highway program in Natuna from several perspectives, namely from the potential of regionalcommodities and infrastructure for Sea Toll services in the Natuna region. The analysis method used is descriptive qualitative and comparative. The results showed that for the cluster of the western region of Indonesian waters, in this case represented bya sample of the T-3 Natuna Islands Sea Toll route service, in terms of supply and demand from the homebase of Tanjung Priok Port, it is sufficiently balanced even though there are several superior commodities in the Natuna archipelago that have not yet optimally distributed, due to the low development and increase in added value of commodities. Based on the sample Sea Toll service route that has been selected for the Western Region of Indonesia, namely the T-3 route for the Natuna Islands region, several criteria that need to be considered in the future regarding the Sea Toll service cluster include regional commodities, Port infrastructure facilities and infrastructure, hinterland transportation facilities and infrastructure, and ship type and capacity

Vehicle Telematics for Safer, Cleaner and More Sustainable Urban Transport: A Review

Urban transport contributes more than a quarter of the global greenhouse gas emissionns that drive climate change; it also produces significant air pollution emissions. Furthermore, vehicle collisions kill and seriously injure 1.35 and 60 million people worldwide, respectively, each year. This paper reviews how vehicle telematics can contribute towards safer, cleaner and more sustainable urban transport. Collection methods are reviewed with a focus on technical challenges, including data processing, storage and privacy concerns. We review how vehicle telematics can be used to estimate transport variables, such as traffic flow speed, driving characteristics, fuel consumption and exhaustive and non-exhaustive emissions. The roles of telematics in the development of intelligent transportation systems (ITSs), optimised routing services, safer road networks and fairer insurance premia estimation are highlighted. Finally, we outline the potential for telematics to facilitate new-to-market urban mobility technologies, signalised intersections, vehicle-to-vehicle (V2V) communication networks and other internet-of-things (IoT) and internet-of-vehicles (IoV) technologies.

EVALUASI RUTE BUS RAPID TRANSIT (BRT) BERDASARKAN ASPEK KETERJANGKAUAN (STUDI KASUS: KOTA SEMARANG)

The transportation system is affected by activity, movement, and network. If a transportation system is unable to keep up with the activities and movements of the community, there will be various transportation system problems such as networks. One of the problems in meeting the needs of the community movement is the uneven range of BRT services. The results of the analysis conducted by researchers based on the results of analysis of existing BRT service routes obtained that 72% of areas in Semarang city are already served, but based on the results of the analysis of brt service route recommendations obtained that 86% of areas in Semarang city are already served brt routes.. Based on the results of the study, there is 1 BRT route recommendation and 3 feeder route recommendations (PP).

A novel and efficient exact technique for integrated staffing, assignment, routing, and scheduling of home care services under uncertainty

We model and solve integrated multi-period staffing, assignment, routing, and scheduling of caregivers for home care services and obtain insights for the case under uncertainty. The goal is to construct a weekly schedule that adheres to related operational considerations and determines optimal staffing of caregivers by minimizing caregivers’ fixed- and overtime costs. For tractability, we incorporate a priori-generated visit pattern—an existing practical approach that deals effectively with hard assignment decisions. First, we propose a novel mixed-integer program (MIP) for the nominal (deterministic) problem. We then incorporate uncertainty in service and travel times and develop a robust counterpart by hybridizing interval and polyhedral uncertainty sets. Second, we show that there is a special mathematical structure within the model that allows us to develop a novel logic-based Benders branching-decomposition algorithm that systematically delays the resolution of difficult routing/ scheduling problems and efficiently solves both the nominal and robust MIP models, i.e., our solution approach for the deterministic case allowed us to solve the robust model. Using a benchmark and newly generated instances from the literature, we show that CPLEX can solve our nominal model with average optimality gap of 56%. On the other hand, our new exact technique can solve our nominal model to an average optimality gap of 5%. Third, we provide practical insights into (i) the price of robustness and (ii) the impacts of nurse flexibility and overtime. The average total cost does not increase beyond 18% than the nominal solution and the cost-savings of nurse flexibility is about 19% on average and higher than overtime’s. We also demonstrate that nurse flexibility impact is high and comparable in both cases, deterministic and stochastic.

Osrm: Interface Between R and the OpenStreetMap-Based Routing Service OSRM

osrm: Interface Between R and the OpenStreetMap-Based Routing Service OSRM

A Development of Optimal Algorithm for Integrated Operation of UGVs and UAVs for Goods Delivery at Tourist Destinations

Although the actual use of delivery robots like UGVs and UAVs has not yet been generalized, they are also used for additional purposes like fun and enjoyment in some limited areas such as tourist destinations. In this study, an optimal algorithm is proposed that operates a delivery service through an integrated system of UGVs and UAVs at certain tourism destination. It is assumed that both UGVs and UAVs or only one means could be used depending on the type of goods delivered and the topographical characteristics. The mathematical model-based optimization technique is applied to generate the delivery service route of both UGVs and UAVs that can maximize total customer satisfaction. The developed mathematical model is solved through CPLEX and genetic algorithm, and the results are compared by dividing into case 1 in which UAVs move freely and case 2 in which UAVs can move only in a limited path since there is a risk of accidental falling when moving. As a result, when UAVs move freely, the total customer satisfaction is higher while the total complete time increases. However, it is suggested that an appropriate operation policy should be determined considering the risk of accidental falling.

Smart City IoT System Network Level Routing Analysis and Blockchain Security Based Implementation.

This paper demonstrates, network-level performance analysis and implementation of smart city Internet of Things (IoT) system with Infrastructure as a Service (IaaS) level cloud computing architecture. The smart city IoT network topology performance is analyzed at the simulation level using the NS3 simulator by extracting most of the performance-deciding parameters. The performance-enhanced smart city topology is practically implemented in IaaS level architecture. The intended smart city IoT system can monitor the principal parameters like video surveillance with a thermal camera (to identify the virus-like COVID-19 infected people), transport, water quality, solar radiation, sound pollution, air quality (O3, NO2, CO, Particles), parking zones, iconic places, E-suggestions, PRO information over low power wide area network in 61.88 km × 61.88 km range. Primarily we have addressed the IoT network-level routing and quality of service (QoS) challenges and implementation level security challenges. The simulation level network topology analysis is performed to improve the routing and QoS. Blockchain technology-based decentralization is adopted to enrich the IoT system performance in terms of security.