说明：  ：目前，粒子群算法在连续问题优化上的应用已经很广泛，然而在离散问题优化方面仍处在尝试阶段。提出了一种改 进粒子群算法来解决矩形件排样优化问题(离散优化问题)。该算法融合了遗传算法中的交叉和变异思想，采用了信息交流 策略，使其达到快速优化目的。算法也对“最低水平线法”解码方式进行了改进。实验结果表明，该算法具有快速、高效特点， 与现有同类算法比较，在解决矩形件排样问题方面的优势明显。
(: At present, the particle swarm optimization algorithm in a row on the issue has very broad applications, but in the discrete optimization problem is still trying to stage. An improved particle swarm optimization to solve the optimization of the rectangular piece nesting problems (discrete optimization problem). The algorithm combines the genetic algorithm crossover and mutation in the thinking of information-sharing strategies used to achieve the purpose of rapid optimization. Algorithm of the " minimum horizontal method" approach to the improvement of decoding. Experimental results show that the algorithm is fast, high-performance characteristics compared with existing similar algorithm, in solving rectangular piece nesting problems have obvious advantages.)