Application of Optimization Algorithms in Design of Railway Vehicles: Review of Selected Methods

The design of modern railway vehicles is increasingly inseparable from advanced computation and programming. As engineering challenges become more complex, sophisticated numerical algorithms and powerful computational tools enable designers to solve problems that would otherwise be difficult, time-consuming, or even impossible to address using conventional methods. The global trend toward algorithm-based design and analysis is rapidly transforming the railway industry. Virtual prototypes and computer simulations have become essential elements of high-quality railway vehicle development. These simulations support a wide range of analyses, including statics, kinematics, dynamics, strength, durability, and reliability, covering both complete vehicles and their individual subsystems. Modern simulation tools can therefore provide comprehensive insight into the mechanical behavior of railway vehicles while also accounting for aspects related to technology, materials, operation, and other key engineering requirements. Against this background, the main objective of this study is to provide a comprehensive overview of computational optimization methods used in railway vehicle design. This study reviews the most widely applied numerical optimization procedures that have established a significant position in contemporary engineering practice and are particularly relevant to railway vehicle designers. The presented work describes the fundamental principles of the optimization process in railway vehicle design and provides a mathematical formulation of optimization problems. Particular attention is given to the optimization of the modal and spectral properties of railway vehicles, as well as to topology optimization, which offers new possibilities for developing lightweight and structurally efficient components. Three representative optimization problems are investigated to demonstrate the practical potential of these methods: the optimization of a corrugated sheet-metal structure, the main load-bearing rectangular profile of an open wagon, and a strut structure supporting the roof of a hopper wagon. In all three cases, the optimization objective was to minimize structural mass while preserving the required functional and mechanical properties. The results demonstrate the considerable potential of computational optimization in railway vehicle design. When an appropriate optimization method is selected and correctly applied, significant reductions in material consumption—and consequently in production costs—can be achieved without compromising the structural performance required for safe and reliable long-term operation. These findings highlight the important role of computational optimization as a powerful tool for developing lighter, more economical, and more efficient railway vehicles.