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Scheduling of Multiple Projects with Resource Constraints Using Genetic Algorithms

机译:遗传算法在资源受限的多个项目调度中的应用

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A scheduling approach using genetic algorithms (GA) was presented to optimize multiple projects for quality project period performance with resource constraints. The model of the approach and key parameters of the algorithm including chromosome encoding and decoding, fitness computation, initial population, selection and crossover were conducted. A precedence feasible list was used in the chromosome encoding and decoding operation to reduce search space. An efficient crossover method was developed to avoid the procedure of chromosome recovery. A comparison was made between the algorithm and a heuristic scheduling method with an example. The result validates the superiority of the approach.
机译:提出了一种使用遗传算法(GA)的计划方法来优化多个项目,以在资源受限的情况下提高项目质量。建立了算法的方法和关键参数模型,包括染色体编码和解码,适应度计算,初始种群,选择和交叉。在染色体编码和解码操作中使用了优先可行列表以减少搜索空间。开发了一种有效的交叉方法来避免染色体恢复的过程。通过一个例子对算法与启发式调度方法进行了比较。结果证实了该方法的优越性。

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