정수계획 모형에서 라그란지안 구조정의 및 완화를 지원하는 지능형 시스템의개발

Development of an intelligent system for Lagrangian structural identification and relaxation for integer programmings

This research investigates the automatic identification of typical embedded structures in the Integer Programming(IP) models and automatic transformation of the problem to an adequate Lagrangian problem which can provide tight bounds within the acceptable run time. For this purpose, the structural distinctiveness of variables, constants, blocks of terms, and constraint chunks is identified to describe the structure of the IP model. To assist the identification of the structural distinctiveness, the representation by the knowledge based IP model formulator UNIK-IP is adopted. For the reasoning for the structural identification, the bottom-up, top-down, and case-based approaches are proposed. A prototype system UNIK-RELAX is developed to implement the approaches proposed in this research.