The embodiment design constraint satisfaction problem of the BOOTSTRAP facing interval analysis and genetic algorithm based decision support tools

Recent progress has been made in the field of digital processing tools based on interval analysis dedicated to decision support in embodiment design. In this paper, the performances of an interval analysis based Constraint Satisfaction Problem (CSP) solver and a Genetic Algorithm based design code are compared and discussed. The embodiment design problem of a Joule–Brayton air conditioning system (Bootstrap) used in aeronautics has been tackled using both approaches. CSP relating to Bootstrap design appear to be difficult due to the size and the complexity of the solution search domain. Design choices are associated with continuous and discrete variable values while the Bootstrap effectiveness is extremely sensitive to most of these design variables. Some numerical results relating to an aircraft air conditioning system are presented.