作者：
Ran HaoDelin LuoHaibin DuanSchool of Reliability and Systems Engineering
Beihang UniversityBeijing100191 China Department of AutomationXiamen UniversityXiamenChina Science and Technology on Aircraft Control LaboratorySchool of Automation Science and Electrical EngineeringBeihang UniversityBeijingChina
Unmanned aerial vehicles (UAVs) have shown their superiority for applications in performing military and civilian *** which,multiple UAVs mission assignment is becoming more important for today's military *** ...
详细信息
ISBN:
(纸本)9781479946983
Unmanned aerial vehicles (UAVs) have shown their superiority for applications in performing military and civilian *** which,multiple UAVs mission assignment is becoming more important for today's military *** far,there have been many bio-inspired computation algorithms for solving multiple UAVs mission assignment problems,including particle swarm optimization (PSO),differential evolution algorithm (DE) and so ***,deficiencies of these approaches exist inevitably,which cannot satisfy the requirements of dynamic mission *** this paper,a new UAV assignment model focusing on the energy consumption of UAV is brought up which can be easily applied to intelligence ***,we propose a new approach by applying the modified Pigeon-Inspired Optimization (PIO) algorithm to sovle the multiple UAVs mission assignment *** simulation results show that the modified PIO algorithm is more effective when compared with other state-of-the-art algorithms in addressing mission assignment problem for multiple UAVs.
Traveling Salesman Problem is one of typical problems of combinatorial optimization. It is because of complexity of TSP that accurate computing couldn't find a global optimal solution in more short time or all. By...
详细信息
ISBN:
(纸本)9781424409723
Traveling Salesman Problem is one of typical problems of combinatorial optimization. It is because of complexity of TSP that accurate computing couldn't find a global optimal solution in more short time or all. By analyzing the relationship between global solutions and local optimal solutions computed using algorithms for TSP, it is found that union set of edge sets multi high-qualify local optimal solutions can include all edges of a,global optimal solution. The method, initial edge set for TSP, is put forward based on statistic principle. The search space of original problem is down greatly by utilizing new method;the quantity of initial edge set is about double times of problem scale. Accurate computing algorithms can find global optimal solution for small scale TSP based on new edge sets, and efficiency of stochastic search algorithms is improved greatly.
Traveling Salesman Problem is one of typical NP-hard problems of combinatorial *** is because of the complexity of TSP that accurate computing algorithms couldn't find a global optimal solution in more short time ...
详细信息
Traveling Salesman Problem is one of typical NP-hard problems of combinatorial *** is because of the complexity of TSP that accurate computing algorithms couldn't find a global optimal solution in more short time or at *** analyzing the relationship between global optimal solutions and local optimal solutions computed using heuristic algorithms for TSP, it is found that union set of edge sets of multi high-qualify local optimal solutions can include all of edges of a global optimal *** method, reducing initial edge set for TSP, is put forward based on probability statistic *** search space of original problem is cut down greatly by utilizing new method;the quantity of new initial edge set is about double times of problem *** computing algorithms can find global optimal solution for small scale TSP based on new edge sets, and efficiency of stochastic search algorithms is improved greatly.
Traditional scheduling strategies base their goals on maximizing the total system throughput. However, in recent research, the maximized total throughput does not necessarily represent the optimal system resource allo...
详细信息
ISBN:
(纸本)078039335X
Traditional scheduling strategies base their goals on maximizing the total system throughput. However, in recent research, the maximized total throughput does not necessarily represent the optimal system resource allocation. In this paper, we propose the Proportional Gradient Satisfaction Strategy (PGSS), which adds user satisfaction value to the existing scheduling criteria. PGSS schedules bandwidth in proportion to the temporal satisfaction gradient rather than original bandwidths used in traditional scheduling strategies. Moreover, PGSS substitutes user satisfaction value with its gradient to simplify the nonlinear problem of satisfaction value,traditionally solved by intelligence algorithms, in order to reduce the algorithm complexity to make PGSS practical to implement in a base station. Simulation shows that compared with proportional compensation algorithm, PGSS promotes the system aggregated satisfaction value and still guarantees the maximized system throughout.
暂无评论