Multiple objective optimisation of composite sandwich structures for rail vehicle floor panels

摘要

This paper describes the application of an ant colony optimisation (ACO) algorithm to the multiple objective optimisation of a rail vehicle floor sandwich panel. The ACO algorithm was used to search a design space that was defined by sandwich theory and a material database in order to identify constructions that were optimal with respect to low mass and low cost. A broad range of mass and cost optimal sandwich material designs were identified successfully. These provided mass savings of up to 60% compared to existing plywood-based flooring systems, although mass savings above 40% had an associated cost premium.