Abstract
Dynamic optimization problems require constant tracking of the optimum. A solution for such a problem has to be adjustable in order to remain optimal as the optimum changes. The manner of changing design parameters to predefined values is dealt with in the field of control. Common control approaches do not consider the optimality of the design, in terms of the objective function, while adjusting to the new solution. This study highlights the issue of the optimality of adaptation, and defines a new optimization problem – ”Optimization of Adaptation”. It is a multiobjective problem that considers the cost of the adaptation and the optimality while the adaptation takes place. An evolutionary algorithm is proposed in order to solve this problem, and it is demonstrated, first, with an academic example, and then with a real life application of a robotic arm control.
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Salomon, S., Avigad, G., Fleming, P.J., Purshouse, R.C. (2013). Optimization of Adaptation - A Multi-objective Approach for Optimizing Changes to Design Parameters. In: Purshouse, R.C., Fleming, P.J., Fonseca, C.M., Greco, S., Shaw, J. (eds) Evolutionary Multi-Criterion Optimization. EMO 2013. Lecture Notes in Computer Science, vol 7811. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37140-0_6
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DOI: https://doi.org/10.1007/978-3-642-37140-0_6
Publisher Name: Springer, Berlin, Heidelberg
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