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首页> 外文期刊>International Journal of Production Research >Multi-objective sequence optimization of PCB component assembly with GA based on the discrete Frechet distance
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Multi-objective sequence optimization of PCB component assembly with GA based on the discrete Frechet distance

机译：基于离散Frechet距离的遗传算法优化PCB组件装配的多目标序列

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摘要

A new mechanism,namely a combination of curve matching method based on the discrete Frechet distance and evolutionary algorithms,is proposed to solve pick-and-place sequence optimisation problems as a multi-objective optimisation problem. The essence of the mechanism is to accomplish the comparison of objective vectors with curve matching method. The objective vector is mapped into the array of points with a binary mapping operator and the discrete Frechet distance is utilised to measure the similarity between the reference array of points and the comparison array of points. The genetic algorithm based on the discrete Frechet distance (FGA) is proposed. To test the new mechanism, together with FGA, three other test algorithms are selected to solve the sequence optimisation problem. The simulation results indicate that FGA outperforms other algorithms. This new mechanism is rational and feasible for multi-objective pick-and-place sequence optimisation problems.
机译：提出了一种基于离散Frechet距离的曲线匹配方法与进化算法相结合的新机制，以解决取放序列优化问题，将其作为多目标优化问题。该机制的实质是用曲线匹配法完成目标矢量的比较。使用二进制映射运算符将目标向量映射到点阵列中，并利用离散的Frechet距离来测量参考点阵列与比较点阵列之间的相似度。提出了基于离散Frechet距离（FGA）的遗传算法。为了测试新机制，与FGA一起，选择了其他三种测试算法来解决序列优化问题。仿真结果表明，FGA优于其他算法。该新机制对于多目标拾放序列优化问题是合理可行的。

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