This study is focused on the maneuver planning problem for a tractor-trailer vehicle in curvy and tiny tunnel. Due to curse of dimensionality, prevalent sampling-and- search-based planners used handle rigid-body well become less efficient when trailer number grows or tunnel narrows. fact also has impacts an optimization-based planner if it counts sampling-and-search-based initial guess warm-sta...

Global query optimization in a multidatabase system (MDBS) is a challenging issue since some local optimization information such as local cost models may not be available at the global level due to local autonomy. It becomes even more difficult when dynamic environmental factors are taken into consideration. In our previous work, a qualitative approach was suggested to build so-called multistat...

Since the classic optimization work in System R, query optimization has completely preceded query evaluation. Unfortunately, errors in cost model parameters such as selectivity estimation compromise the optimality of query evaluation plans optimized at compile time. The only promising remedy is to interleave strategy selection and data access using run-time-dynamic plans. Based on the principle...

The automatic optimization of flow control devices is a delicate issue, due to the drastic computational time related to unsteady high-fidelity flow analyses and the possible multimodality of the objective function. Thus, we experiment in this article the use of kriging-based algorithms to optimize flow control parameters, since these methods have shown their efficiency for global optimization ...

Dynamic optimization can be used to determine optimal input profiles for dynamic processes. Due to plant-model mismatch and disturbances, the optimal inputs determined through model-based optimization will, in general, not be optimal for the plant. Modifier adaptation is a methodology that uses measurements to achieve optimality in the presence of uncertainty. Modifier-adaptation schemes have b...

Run-to-run optimization methodologies exploit the repetitive nature of batch processes to determine the optimal operating policy in the presence of uncertainty. In this paper, a parsimonious parameterization of the inputs is used and the decision variables of the parameterization are updated on a run-to-run basis using a feedback control scheme which tracks signals that are invariant under unce...