  This paper presents an evolutionary algorithm with a new goal-sequence
domination scheme for better decision support in multi-objective optimization.
The approach allows the inclusion of advanced hard/soft priority and constraint
information on each objective component, and is capable of incorporating
multiple specifications with overlapping or non-overlapping objective functions
via logical 'OR' and 'AND' connectives to drive the search towards multiple
regions of trade-off. In addition, we propose a dynamic sharing scheme that is
simple and adaptively estimated according to the on-line population
distribution without needing any a priori parameter setting. Each feature in
the proposed algorithm is examined to show its respective contribution, and the
performance of the algorithm is compared with other evolutionary optimization
methods. It is shown that the proposed algorithm has performed well in the
diversity of evolutionary search and uniform distribution of non-dominated
individuals along the final trade-offs, without significant computational
effort. The algorithm is also applied to the design optimization of a practical
servo control system for hard disk drives with a single voice-coil-motor
actuator. Results of the evolutionary designed servo control system show a
superior closed-loop performance compared to classical PID or RPT approaches.
