In order to resolve the problems of simple genetic algorithm (GA) such as premature convergence,low speed of later convergence and its rough results, this paper analyzes the merits and demerits of the pseudo parallel ...
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In order to resolve the problems of simple genetic algorithm (GA) such as premature convergence,low speed of later convergence and its rough results, this paper analyzes the merits and demerits of the pseudo parallel genetic algorithm (PPGA) and inserts accelerated circulation. Simultaneity,discusses the optimum possibility by using improved PPGA, at last applies to optimization of maintenance planning for existing *** experimental result has confirmed this method *** to GA and PPGA,improved PPGA has good convergence and efficiency in optimizing of maintenance planning for existing *** is a new method for existing bridge's maintenance plan.
Evolutionary algorithm has been used to solve unmanned aerial vehicle(UAV) path planning ***,a UAV path planning problem is modelled as a constrainedoptimization problem,and the goal for evolutionary algorithms is to...
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Evolutionary algorithm has been used to solve unmanned aerial vehicle(UAV) path planning ***,a UAV path planning problem is modelled as a constrainedoptimization problem,and the goal for evolutionary algorithms is to find a collision-free trajectory with respect to the constraints,which requires the algorithms equipping not only a powerful search engine but an effective constraint-handling *** the community of constrainedmulti-objective evolutionary algorithms,an essential idea is how to make good use of the informative infeasible solutions during the evolution process,which can significantly improve performance of the *** the best of our knowledge,this has seldom been explored in UAV path planning *** address this issue,this paper proposes a decomposition-based constrainedmulti-objective evolutionary algorithm with an infeasibility utilization mechanism for solving UAV path planning *** path planning represented by the B-Spline curve is first formulated as a bi-objectiveoptimization problem,i.e.,minimizing the travelling distance and the risk of a UAV,with three constraints including the minimum flight height,the maximum flight height and minimum flight *** a decomposition-based constrainedmulti-objective evolutionary algorithm that can utilize the information containing in infeasible solutions is adopted to solve the constrainedoptimization *** further make good use of the infeasible solutions found by the algorithm,an infeasible utilization mechanism is proposed to guide the search to the optimal *** experimental results have indicated that the proposed algorithm is superior over the compared algorithm in terms of finding a set of well-distributed and well-converged non-dominated solutions.
In this paper, a new algorithm called multi-objective ant-genetic algorithms, which is based on the continuous space optimization is presented to solve constrainedmulti-objective function optimization problems. F...
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ISBN:
(纸本)9781457715860
In this paper, a new algorithm called multi-objective ant-genetic algorithms, which is based on the continuous space optimization is presented to solve constrainedmulti-objective function optimization problems. For the trait of multi-objectiveoptimization, we define the pheromone instruction inheritance searching strategy and the method of pheromone updating. Then we combine four means of pheromone instruction inheritance searching, introduction of excellent decision-making, decision set updating and changing algorithm termination condition together so that the constringent speed of searching has improved a lot and the quantity of Pareto optimal decisions were controlled, also the distributing area of decisions were enlarged, the diversity of the swarm was maintained. At the same time, the termination conditions of multi-objective ant-genetic algorithms were presented. In the end, an example was listed to prove that the algorithms were effective, and it can find a group of widely distributed Pareto optimal decisions.
In order to avoid constructing the penalty function and deleting the good infeasible solutions directly,this paper presents the constrained multi-objective optimization evolutionary algorithm based on the exchange of ...
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In order to avoid constructing the penalty function and deleting the good infeasible solutions directly,this paper presents the constrained multi-objective optimization evolutionary algorithm based on the exchange of pairs of *** algorithm maintains two groups at the same time,one is to save the feasible solutions,the other is to save the infeasible solutions that have some good *** two groups share a number of excellent features and increase the population diversity by the exchange of information of *** results show that the new approach is feasible and effective.
In order to resolve the problems of simple genetic algorithm(GA) such as premature convergence,low speed of later convergence and its rough results,this paper analyzes the merits and demerits of the pseudo parallel ge...
详细信息
In order to resolve the problems of simple genetic algorithm(GA) such as premature convergence,low speed of later convergence and its rough results,this paper analyzes the merits and demerits of the pseudo parallel genetic algorithm(PPGA) and inserts accelerated ***,discusses the optimum possibility by using improved PPGA,at last applies to optimization of maintenance planning for existing *** experimental result has confirmed this method *** to GA and PPGA,improved PPGA has good convergence and efficiency in optimizing of maintenance planning for existing *** is a new method for existing bridge's maintenance plan.
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