In an optimistic parallel simulation, local clocks of different lps must advance at the same rate in order to reduce the number of rollbacks. In this paper, we propose two algorithms for dynamic load balancing which reduce the number of rollbacks in an optimistic PDES system. The first algorithm is based on the load transfer mechanism between lps while the second algorithm, based on the principle of evolutionary strategy, migrates logical processes between several pairs of physical processors. We have implemented both of these algorithms on a cluster of heterogeneous workstations and studied their performance.The experimental results show that the algorithm based on the load transfer is effective when the grain size is larger than 10 milliseconds, and the algorithm based on the process migration yields good performance for grain sizes of 20 milliseconds or larger. In both of these cases the average speed up ranges between 1 and 2 using four processors, when the computation grain-size is within the range of 7 to 50 milliseconds. The reduction in rollback messages as a percentage of the total number of messages due to the algorithms is however around 4% to 8%.