Background: This article reviews recent patents pertaining to the technological achievements
and shortcomings of aircraft Position Indicator and Actuator System (PIAS). Generally, most
patents have concentrated more on design, while implementing various developed single or multiobjective
algorithms to solve component or system optimal design problems such as those of PIAS.
Thus, there is a noticeable lack of patent efforts on either developing new constraint-handling techniques
especially for multi-objective optimization, or applying advance single-objective constrainthandling
techniques to multi-objective optimization.
Method: To address this, the authors of this article in there past work developed a multi-objective optimization algorithm
called Genetic Pareto Set Identification Algorithm plus Different Sex (GPSIA+DS), which considers the feasible and infeasible
solution in it optimization strategy. However, the application of GPSIA+DS to real world reliability engineering
problem has not been validated.
Result: Thus, in this work, GPSIA+DS ability to handle an aircraft PIAS optimization problem was presented. PIAS
component failure rates were obtained via Fault Tree Analysis (FTA). PIAS cost and reliability were the study objective
functions subject to weight constrains. The performance of GPSIA+DS for the test problem was investigated through a
Conclusion: In the comparative study GPSIA+DS was compared with fast-sort genetic algorithm plus constrained dominance
principle (NSGA-II+CD). Although NSGA-II+DS out performed GPSIA+DS for this test problem, it is evident that
GPSIA+DS is equally an efficient algorithm.
Keywords: Aircraft system, constrain, failure rate, genetic algorithm, multi-objective optimization (MOO), pareto set, reliabilityAircraft system, constrain, failure rate, genetic algorithm, multi-objective optimization (MOO), pareto set, reliability
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