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A computational method for the implementation of an evolutionary multi-robotics (EMR) problem in grid computing environments is discussed. Due to the synchronization requirements of evolutionary algorithms (EAs), when the EMR problem is deployed in the grid environment there is a higher waiting time overhead because of medium-grained tasks. The round-robin replication remote work queue (R3Q) is adopted to reduce both the synchronous waiting time and communication time. In the current research, the performance of the grid scheduling is evaluated using uniform computational granularity despite that many problems such as EMR have nonuniform computational granularity. Therefore, in order to evaluate R3Q on nonuniform computational granularity, the cooperative object pushing EMR problem is adopted; and R3Q is compared with grid scheduling algorithms Work Queue (WQ), and list scheduling with round-robin order replication (RR). Our results show that R3Q is effective for tasks which have nonuniform computational granularity.