This paper presents an enhanced group search optimizer (GSO), group search optimizer with intraspecific competition and lévy walk (GSOICLW), to solve the optimal power flow (OPF) problem. GSOICLW s a more biologically realistic algorithm and performs better balance between global and local searching than GSO n hat intraspecific competition IC) and lévy walk (LW) are introduced o GSO. GSOICLW is tested or the OPF problem on the IEEE 30-bus power system, with green house gases emission constraint considered. Simulation results demonstrate the accuracy and reliability of the proposed algorithm, compared with other evolutionary algorithms EAs).

The synthesis and verification of biped walking trajectories during the single-support phase is discussed. The biped is modeled as a seven-link twelve degree-of-freedom anthropomorphic robot. By utilizing the zero moment point (ZMP) and the equivalent force-moment, the physical admissibility of the biped walking is characterized. For physically realizable walking during the single-support phase, the trajectory of the ZMP on the ground must be inside the stable region of the supporting sole. A biped walking trajectory specified by eight pattern parameters is derived through inverse kinematics. ZMP trajectories for different walking patterns and the influence of the pattern parameters on the ZMP trajectories are presented.>