This paper presents a weapon target assignment method to reduce maneuverability overload through redistribution for multi-missile cooperative attack. Firstly, a dynamic constrained model of multi-missile cooperative a...
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This paper presents a weapon target assignment method to reduce maneuverability overload through redistribution for multi-missile cooperative attack. Firstly, a dynamic constrained model of multi-missile cooperative attack on multi-target is established. Secondly, in order to evaluate the missile’s cooperative attack performance better, a cooperative attack probability matrix considering the cooperative attack efficiency is constructed by taking the time-to-go and the line-of-sight rate as *** kinds of maneuvering overload results are compared to verify the effectiveness of redistribution, including unassigned process, primary target assignment and redistribution at the beginning of mid-to-terminal guidance handover. Then, an auction algorithm is used to solve the target assignment problem under multiple constraints. Finally, the simulation results show that the proposed algorithm is much less time-consuming than the existing intelligent optimization algorithms and meets the real-time requirement.
Distributed energy resources installed in the residential areas enable energy consumers to participate in the demand response of distribution systems. In the literature, the algorithms used for the decision-making pro...
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Distributed energy resources installed in the residential areas enable energy consumers to participate in the demand response of distribution systems. In the literature, the algorithms used for the decision-making process of an energy consumer are often centralized and require a dedicated communication link with the power utility. In this paper, a novel decision-making algorithm known as the auction decision process has been proposed. It helps energy consumers to independently meet the demand response in a decentralized manner. The resultant demand response operates in a distributed manner, where the limited information is transmitted among the neighboring consumers using the short-range ZigBee communication. This minimizes the required initial bulk investment for a power utility compared to using a centralized communication system. The data privacy is also improved when compared to the centralized approach. For this work, finding a path with the least transmission loss is selected as the desired constraint for the decision-making process of the demand response. The proposed method has been demonstrated using the IEEE 33 bus systems.
This paper addresses the dispatch problem of fire engines in the event of multiple fires. In *** of the rapid change of fire status with time, the time-varying function is used to describe the change of fire status. T...
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ISBN:
(纸本)9789881563958
This paper addresses the dispatch problem of fire engines in the event of multiple fires. In *** of the rapid change of fire status with time, the time-varying function is used to describe the change of fire status. Then we can treat the fire dispatch problem as a dynamic task allocation problem. Firstly, based on the centralized idea, the depth-first algorithm is used to solve the multi-task assignment problem. Secondly, through this centralized algorithm example simulation, we proposed multi-stage task allocation strategy and designed a new revenue function to improve the auction algorithm. Finally, the effectiveness of the improved auction algorithm is verified by the example simulation.
For the current multi-optical sensor cross-communications algorithm, the main method is the centralized algorithm. However, this algorithm has the characteristics of complex calculation, low effectiveness. Different t...
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ISBN:
(数字)9781510623415
ISBN:
(纸本)9781510623415
For the current multi-optical sensor cross-communications algorithm, the main method is the centralized algorithm. However, this algorithm has the characteristics of complex calculation, low effectiveness. Different types of optical sensors detect the target multi-layer attributes, and based on a predetermined priority sequence, they are finally judged by the global data fusion system, and the level of the target is divided. The target response level function is established by fuzzy algorithm to improve the communication efficiency of the sensor network. Based on the established target response level function, this paper proposes a multi-optical sensor cross-communication algorithm based on auction algorithm. The auction algorithm belongs to a distributed algorithm, and simulation experiments show that the auction algorithm proposed comparing with the centralized algorithm, the auction algorithm has the characteristics of small communication network demand, fast calculation speed, and good convergence and stability of the algorithm.
Based on task allocation of multi-AUV (Autonomous Underwater Vehicle) system, the innovative auction algorithm is applied to hunting task assignments of multi-AUV. The two most decisive factor in the auction algorithm...
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This paper addresses the dispatch problem of fire engines in the event of multiple fires. In view of the rapid change of fire status with time, the time-varying function is used to describe the change of fire status. ...
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This paper addresses the dispatch problem of fire engines in the event of multiple fires. In view of the rapid change of fire status with time, the time-varying function is used to describe the change of fire status. Then we can treat the fire dispatch problem as a dynamic task allocation problem. Firstly, based on the centralized idea, the depth-first algorithm is used to solve the multi-task assignment problem. Secondly, through this centralized algorithm example simulation, we proposed multi-stage task allocation strategy and designed a new revenue function to improve the auction algorithm. Finally, the effectiveness of the improved auction algorithm is verified by the example simulation.
Based on task allocation of multi-AUV (Autonomous Underwater Vehicle) system, the innovative auction algorithm is applied to hunting task assignments of multi-AUV. The two most decisive factor in the auction algorithm...
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ISBN:
(纸本)9781538636749
Based on task allocation of multi-AUV (Autonomous Underwater Vehicle) system, the innovative auction algorithm is applied to hunting task assignments of multi-AUV. The two most decisive factor in the auction algorithm: the election of the auctioneer and the calculation of bidding value. In the traditional auction algorithm, the auctioneer's choice follows the principle of "Who finds the target, who is the auctioneer", but this principle seriously threatens the security and robustness of auction process of the multi-AUV. We propose a new method to determine auctioneer and the method of determining the bidding value of multiple AUV in the auction algorithm, and we have made an essential optimization of the auction algorithm. The final experimental results show that the optimized auction algorithm is compared with the traditional auction algorithm and other hunting tasks allocation algorithms, the security and robustness of the innovative auction has a better effect.
In this paper we analyze the expected time complexity of the auction algorithm for the matching problem on random bipartite graphs. We first prove that if for every non-maximum matching on graph G there exist an augme...
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In this paper we analyze the expected time complexity of the auction algorithm for the matching problem on random bipartite graphs. We first prove that if for every non-maximum matching on graph G there exist an augmenting path with a length of at most 2l + 1 then the auction algorithm converges after N . l iterations at most. Then, we prove that the expected time complexity of the auction algorithm for bipartite matching on random graphs with edge probability p = c log(N) N and c > 1 is O (N log(2)(N)/log(Np)) w.h.p. This time complexity is equal to other augmenting path algorithms such as the HK algorithm. Furthermore, we show that the algorithm can be implemented on parallel machines with O(log(N)) processors and shared memory with an expected time complexity of O(N log(N)). (c) 2014 Wiley Periodicals, Inc.
The bipartite graph matching problem is based on finding a point that maximizes the chances of similarity with another one, and it is explored in several areas such as Bioinformatics and Computer Vision. To solve that...
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ISBN:
(纸本)9781509048441
The bipartite graph matching problem is based on finding a point that maximizes the chances of similarity with another one, and it is explored in several areas such as Bioinformatics and Computer Vision. To solve that matching problem the auction algorithm has been widely used and its parallel implementation is employed to find matching solutions in a reasonable computational time. For example, image analysis may require a large amount of processing, as dense images can have thousands of points to be considered. Furthermore, to exploit the benefits of multicore architectures, a hybrid implementation can be used to deal with communication in both distributed and shared memory. The main goal of this paper is to implement and evaluate the performance of an hybrid parallel auction algorithm for multicore clusters. The experiments carried out analyzes the problem size, the number of iterations to solve the matching and the impact of these parameters in the communication costs and how it affects the execution times.
A combination of dynamic adjustment method and multi-robot task allocation auction algorithm is presented, which is an efficient algorithm to solve task allocation problem of multi-robot cooperative hunting. Firstly, ...
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ISBN:
(纸本)9781509023967
A combination of dynamic adjustment method and multi-robot task allocation auction algorithm is presented, which is an efficient algorithm to solve task allocation problem of multi-robot cooperative hunting. Firstly, this paper optimizes the auction algorithm which can improve the coordination and negotiation performance in multi-robot system and greatly reduce the amount of communication and computation. Secondly, the concept of strengthen learning is introduced into the auction algorithm to facilitate the dynamic task adjustment after the initially allocation which can adapt to the dynamic surroundings well. At last, experimental results show that the proposed algorithm is effective and the performance is better than other similar tasks allocation algorithms.
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