With the increasing concern over environment protection, Economic Emission Dispatch (EED) problem has received much attention. It is essentially a Multi-objective Optimization Problem, which minimizes both fuel cost and emission pollution simultaneously, as well as meets some system limits. This study transforms EED problem to a single-objective problem with weighted sum method, and then use Newton method to solve the equality constraint iteratively and introduce a common penalty function to deal with the inequality constraint. Moreover, this study tries to propose a new meta-heuristic algorithm inspired by kernel tricks to solve EED problem with no hyper parameters to be tuned. The new algorithm can map a non-linear objective function into a linear one with higher-dimension. Thus the optimization process could be transformed into a linear process, which is more likely to get the optimum solution. When applied in the 3 real-world EED cases with valve point, the new algorithm achieved a better performance compared with other algorithms in the literature.

Among qualitative direction relation models, Oriented point relation algebra (OPRA_m) is a remarkable model for robot navigation with uncertain direction information. It has great advantages in providing powerful expressions with very limited information compared with other point-based spatial relation models. The original OPRA_m is defined in 2D space, and its model and reasoning algorithm are found not applicable in 3D space. We proposed a novel direction relation model named OPRA3D_m to extend the original OPRA_m to 3D space, and presented a new reasoning algorithm on Oriented point relation algebra in three dimension (OPRA3D_m). A further study was carried out for composition reasoning on OPRA3D_m. The proposed reasoning algorithm will deduce new information which cannot be directly detected by hardware. The experiment showed the algorithm had some practical significance, it can be applied to the Unmanned aerial vehicle (UAV) navigation and similar scenarios.