The multi-load AGV (Automatic Guided Vehicle) is a new kind of materials handling equipment used to load cloth automatically in an intelligent weaving workshop. It can transport multiple rolls of cloth and choose the ...
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The multi-load AGV (Automatic Guided Vehicle) is a new kind of materials handling equipment used to load cloth automatically in an intelligent weaving workshop. It can transport multiple rolls of cloth and choose the correct, most effective path to improve the transportation efficiency without people engaged in. This paper creates a feasible path topology according to the layout of the workshop and the logistics environment, and uses the Warshall-Floyd algorithm to search for the optimal route between two arbitrary points. The aim of the path planning is to maximize the machine efficiency, which is constrained by environmental limits, load limits and work limits. This paper establishes the mathematical model of the path planning problem using the mixed genetic particle swarm optimization algorithm (ga-pso) to solve the problem, and the particle iteration mechanism based on the time priority is proposed to make the evolution more directional and accelerate the convergence speed of the algorithm. The effectiveness and practicability of the model and methods are verified by simulation and benefit analysis.
The solar array whose quality has great influence on the work efficiency of the spacecraft is the most important power supply system and the honeycomb sandwich panel which has high specific strength and stiffness is t...
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The solar array whose quality has great influence on the work efficiency of the spacecraft is the most important power supply system and the honeycomb sandwich panel which has high specific strength and stiffness is the perfect material for solar *** finite element model(FEM) of the honeycomb sandwich panel includes idealized hypothesis and simplification,which results in the difference between the calculating data and the test *** this paper the honeycomb sandwich panel is equivalent to a structure which can be calculated by NASTRAN based on the equivalence theory and then the improved Genetic- Partical Swarm Optimization(ga-FSO) algorithm is used to update the FEM,the updated precision and efficiency of the ga,pso and ga- pso are compared and the results show that these random search algorithms can update high order modes even use the incomplete low order *** improved ga-pso algorithm can use ga to efficiently search for the global optimal solution at the early stage,and use pso to intensively search for the local optimal solution at the later stage,it has higher searching efficiency and precision,the updated model has good approaching and prediction ability and can be taken as the fiducial model for the following calculation.
The solar array whose quality has great influence on the work efficiency of the spacecraft is the most important power supply system and the honeycomb sandwich panel which has high specific strength and stiffness is t...
详细信息
The solar array whose quality has great influence on the work efficiency of the spacecraft is the most important power supply system and the honeycomb sandwich panel which has high specific strength and stiffness is the perfect material for solar *** finite element model(FEM) of the honeycomb sandwich panel includes idealized hypothesis and simplification,which results in the difference between the calculating data and the test *** this paper the honeycomb sandwich panel is equivalent to a structure which can be calculated by NASTRAN based on the equivalence theory and then the improved Genetic-Partical Swarm Optimization ( ga-pso) algorithm is used to update the FEM,the updated precision and efficiency of the ga,pso and ga-pso are compared and the results show that these random search algorithms can update high order modes even use the incomplete low order *** improved ga-pso algorithm can use ga to efficiently search for the global optimal solution at the early stage,and use pso to intensively search for the local optimal solution at the later stage,it has higher searching efficiency and precision,the updated model has good apprcaching and prediction ability and can be taken as the fiducial model for the following calculation.
In order to get over the insufficiency of back-propagation (BP) algorithm, after analyses of genetic algorithm (ga) and particle swarm optimization (pso), a ga-pso algorithm is proposed. In ga-pso, individuals in a ne...
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ISBN:
(纸本)1424403316
In order to get over the insufficiency of back-propagation (BP) algorithm, after analyses of genetic algorithm (ga) and particle swarm optimization (pso), a ga-pso algorithm is proposed. In ga-pso, individuals in a new generation are created, not only by crossover and mutation operation in ga but also by pso, based on redefine local optimization swarm. So it can both avoid local minimum and has good global search capacity. The performance of ga-pso is compared to both ga and pso in artificial neural networks weight training, demonstrating its superiority.
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