Pattern Search Algorithm for Blackboard-Based Multidisciplinary Design Optimization Frameworks

Abstract

Preliminary aircraft design necessitates the use of a range of analysis tools, which are often scattered among many departments in an organization and require regular tuning from skilled operators. For this reason, a distributed Multidisciplinary Design Optimisation approach that permits individual organizational domains to use their preferred analysis and optimization tools would be most suitable. This paper revisits a Blackboard framework, which uses simple heuristics to automatically guide organizational design domains to a single optimum by narrowing the bounds on the shared design variables. The authors present a newly developed rule base for this legacy framework, which has been given the title “Multidisciplinary Pattern Search.” Two examples, one of which is for conceptual transonic wing design, demonstrate the merit of the newly developed rule base, database, and visualization modules. They also serve as a means for comparisons with two established Multidisciplinary Design Optimisation architectures. The results indicate that the Blackboard performs better than the distributed Collaborative Optimisation approach, albeit worse than the monolithic simultaneous analysis and design method that tends to be organizationally disruptive to implement.