Multi-Objective Optimisation

Multi-Objective Optimisation

The majority of engineering systems or processes require the consideration of multiple, and often conflicting design decisions. Models and CAE tools have enabled design engineers to make these decisions whilst monitoring their impact on multiple, and again conflicting process output metrics such as efficiency, product lifespan and cost.

The MoDS software enables users to apply any CAE tool or model to complete such design exercises to achieve multiple objectives and thus find optimal design solutions.

These are solved through access to optimisation techniques such as Levenberg-Marquardt, Simultaneous Perturbation Stochastic Approximation (SPSA), 2nd order SPSA and Maximum Likelihood Estimation using Bayesian MCMC sampling.

With experimental activities costing up to thousands of dollars per day and with an expanding portfolio of potential technology solutions, the scope of these tests is growing further still. As such employing intelligent design of experiments techniques is proving to be a powerful tool in reducing your overall development costs.