摘要：Inspired by biologic nature of flying wild geese, a so-called process goose queue (PGQ) technique oriented for plant-wide optimization is established. Taking advantage of this ad-hoc structure of flying geese, a plant-wide process can be decomposed into several hierarchically connected PGQs along the direction of the objective function generation. In line with this thought, plant-wide process optimization is accordingly identical with the following and tracking issues between leading and following geese. Followed by this philosophy, related theoretical definitions and modeling principles together with enabling algorithms are explicitly introduced. With the characteristics of evolutionary optimization, PGQ approach is able to overcome the algorithmic deficiencies associated with conventional optimizations. To demonstrate the feasibility and validity of the contributions, TE process is employed as the case study.
