The Way to an Open-Source Software for Automated Optimization and Learning - Open Opal

Abstract

An optimization framework combines various methods, strategies, and programming interfaces on a robust software platform. Its development requires knowledge from application areas, and about optimization methods, as well as from software engineering. Different persons provide diverse know-how about modeling and simulating engineering and/or business problems, about search and optimization methods, and about new software trends to implement them into software. This paper describes the approach how an optimization framework based on evolutionary algorithms and other methods is developed in subsequent projects with application engineers and software developers cooperatively working together guaranteeing a sophisticated knowledge transfer. Therefore, particular knowledge management aspects are emphasized. As result, the optimization platform OpenOpal and the ideas behind its software architecture, supporting the know-how transfer, are presented. In order to continuously improve this optimization framework it is transferred into an open-source software initiative. The objective is to broaden the user group by increasing the number of knowledge contributors both from academia - integrating and testing newly developed optimization methods - and from various engineering areas - providing real-world problems to be solved.