Line-of-balance (LOB) methodology produces a work schedule in which resource allocation is automatically performed to provide a continuous and uninterrupted use of resources, but the distribution of resources could be further improved by resource leveling even if multiple resources are involved. The objective of this study is to develop a genetic algorithm (GA)-based multiresource leveling model for schedules that are established by LOB. The proposed model postulates that the production rate and duration of an activity are governed by the resource that requires the longest duration in completing a unit. Once the LOB schedule is established, resource leveling is performed according to the principle of optimum crew size that makes use of a utility data curve, which shows that productivity will suffer if the crew size is different than the optimum crew size, and the principle of natural rhythm that allows shifting the start times of an activity forward or backward at different units of production by changing the number of crews employed. The duration of an activity in any one unit and the precedence relationships between activities do not change during the leveling procedure. When applied to the LOB schedule of a pipeline project that was used to illustrate the model, it was observed that the proposed multiresource leveling model provided a smoother resource utilization histogram while maintaining optimum productivity.