A unified optimization framework for real world problems

Abstract

In this paper, an object-oriented unified optimization framework (UOF) for general problem optimization is developed. Based on global evolutionary algorithms, numerical deterministic methods, and C++ objective design, the UOF itself has great potential to perform optimization operations on kind of problems. The UOF provides basic interfaces to define a general problem and generic solver;, hence the two different parts are bridged. The UOF components are categorized into problem and solver parts and work independently. Therefore, reutilization of the high level code allows an adaptation to new problem and solver quickly. We customize the UOF to deal with some real world optimization problems.