Efficient airport airside ground movement(AAGM)is key to successful operations of urban air mobility.Recent studies have introduced the use of multi-objective multigraphs(MOMGs)as the conceptual prototype to formulate...Efficient airport airside ground movement(AAGM)is key to successful operations of urban air mobility.Recent studies have introduced the use of multi-objective multigraphs(MOMGs)as the conceptual prototype to formulate AAGM.Swift calculation of the shortest path costs is crucial for the algorithmic heuristic search on MOMGs,however,previous work chiefly focused on single-objective simple graphs(SOSGs),treated cost enquires as search problems,and failed to keep a low level of computational time and storage complexity.This paper concentrates on the conceptual prototype MOMG,and investigates its node feature extraction,which lays the foundation for efficient prediction of shortest path costs.Two extraction methods are implemented and compared:a statistics-based method that summarises 22 node physical patterns from graph theory principles,and a learning-based method that employs node embedding technique to encode graph structures into a discriminative vector space.The former method can effectively evaluate the node physical patterns and reveals their individual importance for distance prediction,while the latter provides novel practices on processing multigraphs for node embedding algorithms that can merely handle SOSGs.Three regression models are applied to predict the shortest path costs to demonstrate the performance of each.Our experiments on randomly generated benchmark MOMGs show that(i)the statistics-based method underperforms on characterising small distance values due to severe overestimation;(ii)A subset of essential physical patterns can achieve comparable or slightly better prediction accuracy than that based on a complete set of patterns;and(iii)the learning-based method consistently outperforms the statistics-based method,while maintaining a competitive level of computational complexity.展开更多
Path marginal cost （PMC） is the change in totaltravel cost for flow on the network that arises when timedependentpath flow changes by 1 unit. Because it is hardto obtain the marginal cost on all the links, the local...Path marginal cost （PMC） is the change in totaltravel cost for flow on the network that arises when timedependentpath flow changes by 1 unit. Because it is hardto obtain the marginal cost on all the links, the local PMC,considering marginal cost of partial links, is normallycalculated to approximate the global PMC. When analyzingthe marginal cost at a congested diverge intersection, ajump-point phenomenon may occur. It manifests as alikelihood that a vehicle may unsteadily lift up （down） inthe cumulative flow curve of the downstream links. Previously,the jump-point caused delay was ignored whencalculating the local PMC. This article proposes an analyticalmethod to solve this delay which can contribute toobtaining a more accurate local PMC. Next to that, we usea simple case to calculate the previously local PMC and themodified one. The test shows a large gap between them,which means that this delay should not be omitted in thelocal PMC calculation.展开更多
Geospatial technology is a useful tool when identifying land corridors for transportation networks. The primary transit corridor between Los Angeles, CA and Las Vegas, NV is Interstate-15, approximately a four-hour au...Geospatial technology is a useful tool when identifying land corridors for transportation networks. The primary transit corridor between Los Angeles, CA and Las Vegas, NV is Interstate-15, approximately a four-hour automobile trip without traffic. Virgin Trains USA LLC proposes an alternative means of travel by constructing a high-speed railway along Interstate-15 connecting Las Vegas and Victorville, CA. This study uses least-cost path analysis to propose an optimized alternative corridor for Virgin Trains’ proposed high-speed railway through a system facilitated road and rail accessibility analysis. Previous research using least-cost path and accessibility methodologies evaluated the results of proposed high-speed railway corridors and the system facilitated accessibility changes by visually inspecting deviations from a planned corridor using single or multiple cost criteria as inputs for a weighted cost surface. However, robust analyses of previous least-cost path studies’ corridors are lacking. This proof-in-concept study proposes a less costly corridor through least-cost path analysis and measures the social impact on the stakeholders of a high-speed railway transportation system through system facilitated accessibility. This study’s proposed alternative corridor is 31% shorter than Virgin Trains’ planned corridor and system facilitated accessibility to Las Vegas, NV is increased in 99.74% of Los Angeles County’s census tracts. These results support this study’s position that geospatial technology can support transportation planning in a comprehensive method that considers the transportation corridor and benefits its stakeholders.展开更多
During path planning, it is necessary to satisfy the requirements of multiple objectives. Multi-objective synthesis is based on the need of flight mission and subjectivity inclination of decision-maker. The decision-m...During path planning, it is necessary to satisfy the requirements of multiple objectives. Multi-objective synthesis is based on the need of flight mission and subjectivity inclination of decision-maker. The decision-maker, however, has illegibility for under- standing the requirements of multiple objectives and the subjectivity inclination. It is important to develop a reasonable cost performance index for describing the illegibility of the decision-maker in multi-objective path planning. Based on Voronoi dia- gram method for the path planning, this paper studies the synthesis method of the multi-objective cost performance index. Ac- cording to the application of the cost performance index to the path planning based on Voronoi diagram method, this paper ana- lyzes the cost performance index which has been referred to at present. The analysis shows the insufficiency of the cost per- formance index at present, i.e., it is difficult to synthesize sub-objective flmctions because of the great disparity of the sub-objective fimctions. Thus, a new approach is developed to optimize the cost performance index with the multi-objective fuzzy optimization strategy, and an improved performance index is established, which could coordinate the weight conflict of the sub-objective functions. Finally, the experimental result shows the effectiveness of the proposed approach.展开更多
The wireless sensor networks (WSN) are formed by a large number of sensor nodes working together to provide a specific duty. However, the low energy capacity assigned to each node prompts users to look at an important...The wireless sensor networks (WSN) are formed by a large number of sensor nodes working together to provide a specific duty. However, the low energy capacity assigned to each node prompts users to look at an important design challenge such as lifetime maximization. Therefore, designing effective routing techniques that conserve scarce energy resources is a critical issue in WSN. Though, the chain-based routing is one of significant routing mechanisms but several common flaws, such as data propagation delay and redundant transmission, are associated with it. In this paper, we will be proposing an energy efficient technique based on graph theory that can be used to find out minimum path based on some defined conditions from a source node to the destination node. Initially, a sensor area is divided into number of levels by a base station based on signal strength. It is important to note that this technique will always found out minimum path and even alternate path are also saved in case of node failure.展开更多
Routing, modulation and spectrum allocation in elastic optical networks is a problem aiming at increasing the capacity of the network. Many algorithms such as shortest path algorithm can be used as the routing section...Routing, modulation and spectrum allocation in elastic optical networks is a problem aiming at increasing the capacity of the network. Many algorithms such as shortest path algorithm can be used as the routing section of this problem. The efficiency of these algorithms is partly based on how the cost of each link is defined. In this study, we considered several basic metrics in cost of network links and compared their effects on the network capacity. In particular, the static costs and the dynamic costs were evaluated and compared. For dynamic scenarios, compared to static scenarios, at least one additional factor, the usage of the links, was added. We further considered a new factor that is based on probability of accommodating the signal at a given time in any given link. The results show that, among them, the shortest path algorithm provides the least blocking probability when the cost is a combination of link length and the abovementioned possibility/usage of the link.展开更多
This paper presents an algorithm for solving Bi-criteria Minimum Cost Dynamic Flow (BiCMCDF) problem with continuous flow variables. The approach is to transform a bi-criteria problem into a parametric one by building...This paper presents an algorithm for solving Bi-criteria Minimum Cost Dynamic Flow (BiCMCDF) problem with continuous flow variables. The approach is to transform a bi-criteria problem into a parametric one by building a single parametric linear cost out of the two initial cost functions. The algorithm consecutively finds efficient extreme points in the decision space by solving a series of minimum parametric cost flow problems with different objective functions. On each of the iterations, the flow is augmented along a cheapest path from the source node to the sink node in the time-space network avoiding the explicit time expansion of the network.展开更多
This paper considers a project scheduling problem with the objective of minimizing resource availability costs appealed to finish al activities before the deadline. There are finish-start type precedence relations amo...This paper considers a project scheduling problem with the objective of minimizing resource availability costs appealed to finish al activities before the deadline. There are finish-start type precedence relations among the activities which require some kinds of renewable resources. We predigest the process of sol-ving the resource availability cost problem （RACP） by using start time of each activity to code the schedule. Then, a novel heuris-tic algorithm is proposed to make the process of looking for the best solution efficiently. And then pseudo particle swarm optimiza-tion （PPSO） combined with PSO and path relinking procedure is presented to solve the RACP. Final y, comparative computational experiments are designed and the computational results show that the proposed method is very effective to solve RACP.展开更多
To utilizing the characteristic of radar cross section （RCS） of the low detectable aircraft, a special path planning algorithm to eluding radars by the variable RCS is presented. The algorithm first gives the RCS ch...To utilizing the characteristic of radar cross section （RCS） of the low detectable aircraft, a special path planning algorithm to eluding radars by the variable RCS is presented. The algorithm first gives the RCS changing model of low detectable aircraft, then establishes a threat model of a ground-based air defense system according to the relations between RCS and the radar range coverage. By the new cost functions of the flight path, which consider both factors of the survival probability and the distance of total route, this path planning method is simulated based on the Dijkstra algorithm, and the planned route meets the flight capacity constraints. Simulation results show that using the effective path planning algorithm, the low detectable aircraft can give full play to its own advantage of stealth to achieve the purpose of silent penetration.展开更多
基金This work was supported by the UK Engineering and Physical Sciences Research Council(grant no.EP/N029496/1,EP/N029496/2,EP/N029356/1,EP/N029577/1,and EP/N029577/2)the joint scholarship of the China Scholarship Council and Queen Mary,University of London(grant no.202006830015).
文摘Efficient airport airside ground movement(AAGM)is key to successful operations of urban air mobility.Recent studies have introduced the use of multi-objective multigraphs(MOMGs)as the conceptual prototype to formulate AAGM.Swift calculation of the shortest path costs is crucial for the algorithmic heuristic search on MOMGs,however,previous work chiefly focused on single-objective simple graphs(SOSGs),treated cost enquires as search problems,and failed to keep a low level of computational time and storage complexity.This paper concentrates on the conceptual prototype MOMG,and investigates its node feature extraction,which lays the foundation for efficient prediction of shortest path costs.Two extraction methods are implemented and compared:a statistics-based method that summarises 22 node physical patterns from graph theory principles,and a learning-based method that employs node embedding technique to encode graph structures into a discriminative vector space.The former method can effectively evaluate the node physical patterns and reveals their individual importance for distance prediction,while the latter provides novel practices on processing multigraphs for node embedding algorithms that can merely handle SOSGs.Three regression models are applied to predict the shortest path costs to demonstrate the performance of each.Our experiments on randomly generated benchmark MOMGs show that(i)the statistics-based method underperforms on characterising small distance values due to severe overestimation;(ii)A subset of essential physical patterns can achieve comparable or slightly better prediction accuracy than that based on a complete set of patterns;and(iii)the learning-based method consistently outperforms the statistics-based method,while maintaining a competitive level of computational complexity.
文摘Path marginal cost （PMC） is the change in totaltravel cost for flow on the network that arises when timedependentpath flow changes by 1 unit. Because it is hardto obtain the marginal cost on all the links, the local PMC,considering marginal cost of partial links, is normallycalculated to approximate the global PMC. When analyzingthe marginal cost at a congested diverge intersection, ajump-point phenomenon may occur. It manifests as alikelihood that a vehicle may unsteadily lift up （down） inthe cumulative flow curve of the downstream links. Previously,the jump-point caused delay was ignored whencalculating the local PMC. This article proposes an analyticalmethod to solve this delay which can contribute toobtaining a more accurate local PMC. Next to that, we usea simple case to calculate the previously local PMC and themodified one. The test shows a large gap between them,which means that this delay should not be omitted in thelocal PMC calculation.
文摘Geospatial technology is a useful tool when identifying land corridors for transportation networks. The primary transit corridor between Los Angeles, CA and Las Vegas, NV is Interstate-15, approximately a four-hour automobile trip without traffic. Virgin Trains USA LLC proposes an alternative means of travel by constructing a high-speed railway along Interstate-15 connecting Las Vegas and Victorville, CA. This study uses least-cost path analysis to propose an optimized alternative corridor for Virgin Trains’ proposed high-speed railway through a system facilitated road and rail accessibility analysis. Previous research using least-cost path and accessibility methodologies evaluated the results of proposed high-speed railway corridors and the system facilitated accessibility changes by visually inspecting deviations from a planned corridor using single or multiple cost criteria as inputs for a weighted cost surface. However, robust analyses of previous least-cost path studies’ corridors are lacking. This proof-in-concept study proposes a less costly corridor through least-cost path analysis and measures the social impact on the stakeholders of a high-speed railway transportation system through system facilitated accessibility. This study’s proposed alternative corridor is 31% shorter than Virgin Trains’ planned corridor and system facilitated accessibility to Las Vegas, NV is increased in 99.74% of Los Angeles County’s census tracts. These results support this study’s position that geospatial technology can support transportation planning in a comprehensive method that considers the transportation corridor and benefits its stakeholders.
文摘During path planning, it is necessary to satisfy the requirements of multiple objectives. Multi-objective synthesis is based on the need of flight mission and subjectivity inclination of decision-maker. The decision-maker, however, has illegibility for under- standing the requirements of multiple objectives and the subjectivity inclination. It is important to develop a reasonable cost performance index for describing the illegibility of the decision-maker in multi-objective path planning. Based on Voronoi dia- gram method for the path planning, this paper studies the synthesis method of the multi-objective cost performance index. Ac- cording to the application of the cost performance index to the path planning based on Voronoi diagram method, this paper ana- lyzes the cost performance index which has been referred to at present. The analysis shows the insufficiency of the cost per- formance index at present, i.e., it is difficult to synthesize sub-objective flmctions because of the great disparity of the sub-objective fimctions. Thus, a new approach is developed to optimize the cost performance index with the multi-objective fuzzy optimization strategy, and an improved performance index is established, which could coordinate the weight conflict of the sub-objective functions. Finally, the experimental result shows the effectiveness of the proposed approach.
文摘The wireless sensor networks (WSN) are formed by a large number of sensor nodes working together to provide a specific duty. However, the low energy capacity assigned to each node prompts users to look at an important design challenge such as lifetime maximization. Therefore, designing effective routing techniques that conserve scarce energy resources is a critical issue in WSN. Though, the chain-based routing is one of significant routing mechanisms but several common flaws, such as data propagation delay and redundant transmission, are associated with it. In this paper, we will be proposing an energy efficient technique based on graph theory that can be used to find out minimum path based on some defined conditions from a source node to the destination node. Initially, a sensor area is divided into number of levels by a base station based on signal strength. It is important to note that this technique will always found out minimum path and even alternate path are also saved in case of node failure.
文摘Routing, modulation and spectrum allocation in elastic optical networks is a problem aiming at increasing the capacity of the network. Many algorithms such as shortest path algorithm can be used as the routing section of this problem. The efficiency of these algorithms is partly based on how the cost of each link is defined. In this study, we considered several basic metrics in cost of network links and compared their effects on the network capacity. In particular, the static costs and the dynamic costs were evaluated and compared. For dynamic scenarios, compared to static scenarios, at least one additional factor, the usage of the links, was added. We further considered a new factor that is based on probability of accommodating the signal at a given time in any given link. The results show that, among them, the shortest path algorithm provides the least blocking probability when the cost is a combination of link length and the abovementioned possibility/usage of the link.
文摘This paper presents an algorithm for solving Bi-criteria Minimum Cost Dynamic Flow (BiCMCDF) problem with continuous flow variables. The approach is to transform a bi-criteria problem into a parametric one by building a single parametric linear cost out of the two initial cost functions. The algorithm consecutively finds efficient extreme points in the decision space by solving a series of minimum parametric cost flow problems with different objective functions. On each of the iterations, the flow is augmented along a cheapest path from the source node to the sink node in the time-space network avoiding the explicit time expansion of the network.
基金supported by the National Natural Science Foundation of China(7120116671201170)
文摘This paper considers a project scheduling problem with the objective of minimizing resource availability costs appealed to finish al activities before the deadline. There are finish-start type precedence relations among the activities which require some kinds of renewable resources. We predigest the process of sol-ving the resource availability cost problem （RACP） by using start time of each activity to code the schedule. Then, a novel heuris-tic algorithm is proposed to make the process of looking for the best solution efficiently. And then pseudo particle swarm optimiza-tion （PPSO） combined with PSO and path relinking procedure is presented to solve the RACP. Final y, comparative computational experiments are designed and the computational results show that the proposed method is very effective to solve RACP.
文摘To utilizing the characteristic of radar cross section （RCS） of the low detectable aircraft, a special path planning algorithm to eluding radars by the variable RCS is presented. The algorithm first gives the RCS changing model of low detectable aircraft, then establishes a threat model of a ground-based air defense system according to the relations between RCS and the radar range coverage. By the new cost functions of the flight path, which consider both factors of the survival probability and the distance of total route, this path planning method is simulated based on the Dijkstra algorithm, and the planned route meets the flight capacity constraints. Simulation results show that using the effective path planning algorithm, the low detectable aircraft can give full play to its own advantage of stealth to achieve the purpose of silent penetration.
