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About

C. Hocaoglu is a robotics and computational intelligence researcher whose work has made significant contributions to the field of autonomous path planning and evolutionary optimization. Best known for pioneering the application of genetic algorithms to multidimensional path planning, Hocaoglu developed innovative approaches that eliminate the need for explicit configuration space computation — a longstanding computational bottleneck in robot motion planning. His most influential work, "Planning multiple paths with evolutionary speciation" (2001), has garnered 108 citations and introduced a multiresolution path representation framework combined with evolutionary speciation techniques to solve complex multimodal optimization problems. This foundational contribution was complemented by his earlier development of the Minimal Representation Size Cluster Genetic Algorithm (MRSC GA), first presented in 1997, which provided a principled hypothesize-and-test paradigm for multimodal function optimization. Across a series of closely related publications from 1997 to 2002, Hocaoglu systematically extended these methods to mobile robots, piano-mover problems, and multi-link manipulators. With a cumulative citation count exceeding 200, his body of work remains a valued reference for researchers exploring evolutionary computation and autonomous robotic navigation.