In this paper we focus on an unrelated parallel workgroup scheduling problem where each workgroup is composed of a number of personnel with similar work skills which has eligibility and human resource constraints. The most difference from the general unrelated parallel machine scheduling with resource constraints is that one workgroup can process multiple jobs at a time as long as the resources are available, which means that a feasible scheduling scheme is impossible to get if we consider the processing sequence of jobs only in time dimension. We construct this problem as an integer programming model with the objective of minimizing makespan. As it is incapable to get the optimal solution in the acceptable time for the presented model by exact algorithm, meta-heuristic is considered to design. A pure genetic algorithm based on special coding design is proposed firstly. Then a hybrid genetic algorithm based on bin packing strategy is further developed by the consideration of transforming the single workgroup scheduling to a strip-packing problem. Finally, the proposed algorithms, together with exact approach, are tested at different size of instances. Results demonstrate that the proposed hybrid genetic algorithm shows the effective performance.

在本文中，我们关注于一个无关的并行工作组调度问题，其中每个工作组均由具有相似工作技能且具有资格和人力资源限制的许多人员组成。与具有资源限制的一般无关并行机器调度的最大区别在于，只要有资源可用，一个工作组就可以一次处理多个作业，这意味着如果考虑处理的顺序，就不可能获得可行的调度方案。仅在时间维度上工作。我们将这个问题构造为一个整数规划模型，目的是最小化制造时间。由于无法通过精确算法在给出的模型的可接受时间内获得最优解，因此考虑采用元启发式方法进行设计。首先提出了一种基于特殊编码设计的纯遗传算法。然后，考虑到将单个工作组调度转换为带包装问题，进一步开发了基于箱装策略的混合遗传算法。最后，在不同大小的实例上测试了所提出的算法以及精确的方法。结果表明，提出的混合遗传算法具有良好的性能。