多目标动态优化与遗传算法自动泊车(全英文)

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多目标动态优化与遗传算法自动泊车AbstractThis paper addresses the problem of automatic
parking by a back-wheel drive vehicle， using a biomimetic
model based on direct coupling between vehicle perceptions
and actions. This problem is solved by means of a bio-inspired
approach in which the vehicle controller does not need to
know the car kinematics and dynamic， neither does it call for
a priori knowledge of the environment map. The key point in
the proposed approach is the definition of performance indi-ces that for automatic parking happen to be functions of the
strategic orientations to be injected， in real time， to the car-like robot controller. This solution leads to a dynamic multi-objective optimization problem， which is extremely hard to
be dealt analytically. A genetic algorithm is therefore ap-plied， thanks to which we obtain a very simple and efficient
solution.
1 Introduction
Optimization is one of the most common and pervasive issues
in real-world engineering and economic systems and it is at
the heart of any decision-making task in which a choice must
be made between several alternatives to achieve multiple，
sometimes conflicting， objectives. The objectives are gener-ally formalized as analytical functions or performance indi-ces.
The technical literature on optimization methods is re-ally extensive， as this fundamental subject has received a
tremendous amount of attention since it came of age about
50 years ago. Single-objective optimization is by far the most
researched problem in this field， although many real-life sit-uations are multi-objective optimization problems per se