Dezineforce’s design search and optimisation capabilities are an essential tool for companies performing advanced, high-value and high-performance design. These tools support the designer in the systematic search for better designs by enabling them to gain insights into design behaviour and their improvement. At all times the designer remains in control, able to exercise engineering design judgement and make the right design decisions.

Extensive design search and optimisation approaches

The Dezineforce optimisation toolset covers the following main algorithmic approaches to optimisation and their hybrid variations.

• Hill-climbing methods
• Gradient-based methods
• Evolutionary methods
• Design of experiment
• Response Surface methods

Hybrid optimisation

Dezineforce supports hybrid optimisation approaches that combine more than one of these algorithmic approaches. Such hybrid methods can yield considerable insight into the robustness of the design, particularly when the design’s performance is subject to a variety of conflicting operational requirements.

Hybrid algorithms assist the designer by initially casting a wide view over an objective function that might be expensive to calculate. The ability to focus on specific parameter values that improve the design significantly is very helpful to narrow the scope for a design solution. Once a narrow region of maximum potential is identified, the designer can then zero in to locate the best design.

At each stage the designer gains further insight into the design and the Dezineforce tools helps to make further choices to improve it.

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