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ripple spreading algorithm: a new method for solving multi-objective shortest path problems with mixed time windows

COMPLEX & INTELLIGENT SYSTEMS 2024年第2期10卷 2299-2325页

作者： Yu, Shilin Song, Yuantao Univ Chinese Acad Sci Sch Emergency Management Sci & Engn Beijing 100049 Peoples R China

In emergency management, the transportation scheduling of emergency supplies and relief personnel can be regarded as the multi-objective shortest path problem with mixed time window (MOSPPMTW), which has high requirements for timeliness and effectiveness, but the current solution algorithms cannot simultaneously take into account the solution accuracy and computational speed, which is very unfavorable for emergency path decision-making. In this paper, we establish MOSPPMTW matching emergency rescue scenarios, which simultaneously enables the supplies and rescuers to arrive at the emergency scene as soon as possible in the shortest time and at the smallest cost. To solve the complete Pareto optimal surface, we present a ripple spreading algorithm (RSA), which determines the complete Pareto frontier by performing a ripple relay race to obtain the set of Pareto optimal path solutions. The proposed RSA algorithm does not require an initial solution and iterative iterations and only needs to be run once to obtain the solution set. Furthermore, we prove the optimality and time complexity of RSA and conduct multiple sets of example simulation experiments. Compared with other algorithms, RSA performs better in terms of computational speed and solution quality. The advantage is especially more obvious in the computation of large-scale problems. It is applicable to various emergency disaster relief scenarios and can meet the requirements of fast response and timeliness.

关键词： Emergency rescue ripple spreading algorithm Mixed time windows Multi-objective shortest path problem Pareto optimal paths

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A ripple spreading algorithm for Free-Flight Route Optimization in Dynamical Airspace

A Ripple Spreading Algorithm for Free-Flight Route Optimizat...

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IEEE Symposium Series on Computational Intelligence (IEEE SSCI)

作者： Zhou, Hang Hu, Xiao-Bing Civil Aviat Univ China CAUC Sino European Inst Aviat Engn Tianjin Peoples R China CAUC CAUC ENAC Joint Res Ctr Appl Math ATM Tianjin Peoples R China CAUC Coll Elect Informat & Automat Tianjin Peoples R China

ISBN: (纸本)9781728125473

To resolve the problem of insufficient air routes in the near future, the concept of free flight gives a new solution that all aircraft are allowed to fly their optimal routes. This promising approach would improve the current economic, environmental and safety problems of civil aviation operations. In this paper, a ripple spreading algorithm is proposed for optimizing the aircraft free-flight route in a dynamical airspace. First, the problem description and a mathematical model are presented. Moving adverse weather areas, restricted zones, and time-variant airflow characteristics are taken into account in the airspace. Second, a ripple spreading algorithm adapted to a dynamically weighted network is introduced. The optimal flight route can be achieved by a single run of this efficient method. Finally, a numerical experiment is performed to show the effectiveness of the reported method in optimizing the free-flight route in a given complex dynamical airspace.

关键词： flight route optimization ripple spreading algorithm dynamical airspace free flight wind-optimal

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Research on 3D layered visibility graph route network model and multi-objective path planning for UAVs in complex urban environments

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AEROSPACE SCIENCE AND TECHNOLOGY 2025年 159卷

作者： Hu, Xiao-Bing Yang, Chang-Shu Zhou, Jun Zhang, Ying-Fei Ma, Yi-Ming Civil Aviat Univ China Coll Safety Sci & Engn Lab Complex Syst Safety & Intelligent Decis Tianjin 300300 Peoples R China Civil Aviat Univ China Sino European Inst Aviat Engn Tianjin 300300 Peoples R China Beijing Union Univ Collaborat Innocat Ctr eTourism Beijing 100101 Peoples R China Univ Warwick Sch Engn Coventry CV4 7AL England Shanghai Aircraft Design & Res Inst Shanghai 201210 Peoples R China Beihang Univ Sch Econ & Management Beijing 100191 Peoples R China

Over the past decade, unmanned aerial vehicles (UAVs) have seen increased use in urban transportation, including applications such as package delivery and emergency rescue. However, the complex nature of urban environments poses significant challenges to the safe and efficient operation of UAVs. Path planning offers an effective solution for improving both flight efficiency and safety. This paper develops a novel flight path optimization method that accounts for the configuration of urban environments, as well as critical operational constraints, such as obstacle avoidance and flight altitude limitations. The urban environment is modeled as a 3D layered visibility graph network by deforming urban buildings to cuboid obstacles and representing the obstacles with discrete sampling points. To mitigate potential collision risks between UAVs, maneuvering protection zones (MPZs) are integrated into the network. The objective of this study is to simultaneously minimize path length and maximize the path confidence level, with the latter being a comprehensive assessment of safety, reliability, and public acceptance. To solve the proposed multi-category multi-objective path optimization problem, an improved ripple-spreading algorithm (RSA) is developed, which is theoretically proven to provide the exact and complete Pareto-optimal solution set. Simulation tests, performed on both artificially generated problems and the urban area of Shenzhen, China, demonstrate that the inclusion of MPZs reduces the computing time by 70% while increasing the average shortest path length by only 1%. In addition, compared to other existing algorithms, RSA demonstrates high efficiency in identifying the complete Pareto frontier in large-scale networks.

关键词： Urban air mobility (UAM) Unmanned aerial vehicles (UAVs) Route network design 3D visibility graph Multi-category multi-objective path planning ripple spreading algorithm

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Distribution network disaster recovery strategy considering road risk based on multi-source coordination strategy

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ELECTRIC POWER SYSTEMS RESEARCH 2024年 229卷

作者： Zhou, Yangye Wang, Guoqing Wu, Zhongqi Zhu, Jianming Huang, Jun Univ Chinese Acad Sci Sch Engn Sci Beijing 100049 Peoples R China Univ Chinese Acad Sci Sch Emergency Management Sci & Engn Beijing 100049 Peoples R China

With the frequent occurrence of sudden natural disasters, there are more and more disaster events in distribution network, so the research on improving the resilience of distribution network after disaster has attracted increasing interest. Considering the diversity of emergency recovery resources in post-disaster distribution networks, this paper proposes a power grid resilience enhancement model based on multi-source coordination strategy, which comprehensively considers the synergistic effects of distribution line topology, distributed generator(DG) equipment and mobile power sources(MPS). In order to solve the problem that the scheduling strategy is difficult to implement due to the influence of transportation roads, this paper considers the risk problem of transportation lines on the basis of transportation distance factors, and uses ripple spreading algorithm(RSA) to calculate the Pareto front of transportation routes, which is used as an alternative set of transportation routes for MPS equipment. Finally, the IEEE 33-node model is used to verify the effectiveness of the proposed model, the importance of considering transport road risk for actual resource scheduling, and the advantages of RSA in terms of speed and accuracy. The results show that the model can effectively solve the optimal scheduling strategy according to the decision maker's risk preference.

关键词： Distribution network Mobile power sources Transport road risk Multi -source coordination ripple spreading algorithm

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A New City Air Terminal Service Mode: Urban Mobile Station for Luggage Check-in Service and Evolutionary Approach

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2022年第7期23卷 7281-7297页

作者： Zhou, Hang Hu, Xiao-Bing Zhou, Jun Gu, Sheng-Hao Wang, Tian-Qi Civil Aviat Univ China CAUC Sino European Inst Aviat Engn Tianjin 300300 Peoples R China Civil Aviat Univ China CAUC CAUC ENAC Joint Res Ctr Appl Math ATM Tianjin 300300 Peoples R China Civil Aviat Univ China CAUC Coll Elect Informat & Automat Tianjin 300300 Peoples R China

In order to overcome the demerits of traditional city air terminals (CAT), a brand-new service mode based on urban mobile stations (UMS) is introduced in this article for providing the luggage check-in service in urban area. Different from CAT, for each service time period, the UMSs are located based on the real-time passenger distributions. The objectives are to improve the service quality and enhance the competitiveness of air transportation. First, the system components and operation mode of UMS are described. Second, a mathematical model is set up for locating UMSs and assigning passengers to service stations. Three aspects, including the average path length from passengers to UMSs, the maximum acceptable path length for passengers, and the maximum service capacity of a station are considered. Third, to meet the strict time requirement of the UMS system, an effective evolutionary algorithm for optimizing UMS locations in real time is further developed. In the method, the ripple-spreading algorithm is applied for solving the many-to-many path optimization problem and a two-stage adaptive genetic algorithm is utilised for efficiently locating UMSs. Finally, a test case is set up based on the city centre of Tianjin, China, and passenger source locations are obtained by surveying passengers at Tianjin Airport. The reported method is then applied to dynamically locate UMSs in Tianjin urban area and it is compared to some other existing methods to show its effectiveness and efficiency. The service quality of UMS is compared to CAT in both cases with realistic data and randomly generated data to show its advantages.

关键词： Urban mobile station city air terminal luggage check-in service hybrid evolutionary method ripple spreading algorithm adaptive genetic algorithm

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An Efficient Genetic Method for Multi-Objective Location Optimization of Multiple City Air Terminals

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IEEE ACCESS 2021年 9卷 108665-108674页

作者： Zhou, Hang Hu, Xiao-Bing Zhou, Jun Yang, Hongji Civil Aviat Univ China Sino European Inst Aviat Engn Airport Comprehens Transportat Res Inst Tianjin 300300 Peoples R China Civil Aviat Univ China Coll Safety Sci & Engn CAUC ENAC Joint Res Ctr Appl Math Air Traff Manag Tianjin 300300 Peoples R China Beijing Union Univ Collaborat Innovat Ctr eTourism Beijing 100101 Peoples R China Univ Warwick Sch Engn Coventry CV4 7AL W Midlands England Univ Leicester Sch Informat Leicester LE1 7RH Leics England

Some airports construct several buildings in city centre to offer check in and other services, denoted as city air terminals, which help passengers to check in and drop off luggage closer to their residences. Multi-objective location optimization methods play an important role in planning the locations of city air terminals. The objectives are to improve passenger experience and enhance the competitiveness of air transportation. A mathematical model of this problem is introduced. The model takes three factors into accounted as the optimization objectives, including the average path length from passengers to city air terminals, the maximum tolerable distance of passengers, and the service capacity of a station. Secondly, an efficient hybrid evolutionary method is presented for efficiently optimizing the locations of city air terminals, which includes an improved ripple-spreading algorithm for solving the many-to-many path optimization problem and a genetic algorithm for optimizing the facility location problem. Finally, a case study based on a large city in China is performed to test the proposed method for locating city air terminals in urban area and to show its effectiveness and efficiency.

关键词： Cats Urban areas Optimization Airports Roads Mathematical model Genetic algorithms Evolutionary computation genetic algorithm transportation ripple spreading algorithm

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Many-to-Many Path Planning for Emergency Material Transportation in Dynamic Environment

Many-to-Many Path Planning for Emergency Material Transporta...

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IEEE Symposium Series on Computational Intelligence (IEEE SSCI)

作者： Meng, Xiang-Zhi Zhou, Hang Hu, Xiao-Bing Civil Aviat Univ China Sino European Inst Aviat Engn Tianjin Peoples R China Civil Aviat Univ China Coll Elect Informat & Automat Tianjin Peoples R China

ISBN: (纸本)9781728125473

The problem of emergency material transportation in dynamic environment requires to find optimal path between multiple emergency material storage nodes and distribution nodes in a changing routing environment, so as to guarantee the supply of materials within the shortest time. It corresponds to a many-to-many path planning problem in dynamic routing network. The existing static plan optimization and dynamic path optimization method are difficult to ensure the theoretical optimality of the solution in a dynamic disaster environment, and may lead to the failure of emergency material transportation. In this paper, a method of co-evolutionary path optimization is proposed and improved to resolve the many-to-many path planning problems. The ripple diffusion algorithm completes the search process in the form of a ripple diffusion relay race in a given routing environment. Furthermore, the co-evolutionary path optimization method combines the ripple diffusion process with the routing environment change process. When different ripples compete with each other, the routing environment changes dynamically at the same time. Finally, the theoretical optimal solution is obtained in just a single off-line operation. The experimental results show that the co-evolutionary path optimization method has advantages over the traditional method in success rate, solving time, optimality, and flexibility.

关键词： Co-Evolutionary Path Optimization ripple spreading algorithm Path Planning Typhoon Dynamic Environment

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AN EFFECTIVE HYBRID algorithm FOR REAL-TIME OPTIMIZING LOCATIONS OF URBAN MOBILE STATIONS FOR LUGGAGE CHECK-IN SERVICE

AN EFFECTIVE HYBRID ALGORITHM FOR REAL-TIME OPTIMIZING LOCAT...

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Integrated Communications Navigation and Surveillance Conference (ICNS)

作者： Zhou, Hang Hu, Xiao-Bing Civil Aviat Univ China CAUC Sino European Inst Aviat Engn SIAE Tianjin Peoples R China CAUC CAUC ENAC Joint Res Ctr Appl Math Air Traff Manag Tianjin Peoples R China CAUC Coll Elect Informat & Automat Tianjin Peoples R China

ISBN: (纸本)9781728172705

In order to overcome the demerits of traditional city air terminals, a new service mode based on urban mobile stations for providing the urban luggage check-in service is proposed in this study. The station locations are dynamically allocated based on the real-time passenger distribution. Three aspects including the average distance from passengers to urban mobile stations, the maximum tolerable distance, and the maximum service capacity are considered. An effective hybrid algorithm is developed, in which the ripple-spreading algorithm is applied for solving many-to-many path optimization problems and an adaptive genetic algorithm is developed for locating stations. In a case study of Tianjin, China, the proposed method is applied to allocate the urban mobile stations. The service performance of the new mode is compared with that of the traditional city air terminals mode to show the advantages.

关键词： Hybrid evolutionary method ripple spreading algorithm adaptive genetic algorithm urban mobile station luggage check-in service

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