The loading problem in a Flexible Manufacturing System (FMS) involves allocating operations and associated cutting tools to machines for a given set of parts. There may be different environments for the loading problem that result from three ways of grouping machines in an FMS, i.e., no grouping, partial grouping, and total grouping. Unlike most previous studies on the loading problem for the configurations of no grouping and total grouping, this paper focuses on the loading problem resulting from partial grouping, in which each machine is tooled differently but each operation can be processed by one or more machines. Two types of heuristic algorithms are suggested for the loading problem with the objective of minimizing the maximum workload of the machines. Performances of the suggested loading algorithms are tested on randomly generated test problems and the results show that the suggested algorithms perform better than existing ones. In addition, it is found from simulation experiments that loading plans from partial grouping give significantly better performance than those from total grouping.