This paper describes the conceptual framework of a general strategy for developing an engine crankshaft based on computer-aided innovation, together with an introduction to the methodologies from which our strategy evolves. It begins with a description of two already popular disciplines, which have their roots in computer science and natural evolution: evolutionary design (ED) and genetic algorithms (GAs). A description of some optimization processes in the field of mechanical design is also presented. We explain our approach to multi-objective optimization and show how tools like the Pareto diagram can help in identifying conflicts. The concepts presented here are exemplified through the optimization of a combustion engine crankshaft. The main premise of the paper is the possibility to optimize the imbalance of a crankshaft using tools developed in this methodology. This study brings together techniques that have their origins in the fields of optimization and new tools for innovation. We reflect on how computers can have an active role in the conceptual design process, and explain how TRIZ (Theory of inventive Problem Solving) can enrich the discipline of ED. The aim of our research is to extend the search for solutions with GAs and present creative, innovative alternatives to the designer. Similarities between GAs and TRIZ regarding ideality and evolution are presented. We also explain how geometric optimization systems (size, shape, topology and topography) offer hints about the next generation of optimization tools. The role of splines in this context is found to be closely integrated with GAs in enabling this development on a computer-aided design and engineering (CAD&CAE) software interface, and in enabling integration with Java programming language for automation of the development. (C) 2009 Elsevier B.V. All rights reserved.