Multiobjective shape design in a ventilation system with a preference-driven surrogate-assisted evolutionary algorithm
Multiobjective shape design in a ventilation system with a preference-driven surrogate-assisted evolutionary algorithm
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DOI：
10.1145/3321707.3321745
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发表时间：
2019-07
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影响因子：
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通讯作者：
Tinkle Chugh;T. Krátký;K. Miettinen;Yaochu Jin;P. Makkonen
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作者：
Tinkle Chugh;T. Krátký;K. Miettinen;Yaochu Jin;P. Makkonen
利用基于偏好的代理辅助进化多目标优化算法，建立并求解了拖拉机驾驶室进气通风系统的实际外形设计优化问题。我们的动机是实用性，并关注行业从业者面临的两个主要挑战：1)对反映决策者需求的优化问题进行有意义的表述；2)在解决具有计算代价较高的函数评估的问题时，根据决策者的偏好找到理想的解决方案。对于第一个挑战，我们描述了使用商业模拟工具对进气通风系统中的组件进行建模的过程。要解决的问题涉及耗时的计算流体力学模拟。因此，对于第二个挑战，我们扩展了最近提出的Kriging辅助进化算法K-RVEA，以纳入决策者的偏好。数值结果表明，该方法能有效地利用现有的计算资源，所得到的解很好地反映了决策者的偏好。实际上，有两个解决方案主导了基线设计(由决策者在优化过程之前提供的设计)。决策者对结果感到满意，最终选择了一个作为最终解决方案。
We formulate and solve a real-world shape design optimization problem of an air intake ventilation system in a tractor cabin by using a preference-based surrogate-assisted evolutionary multi-objective optimization algorithm. We are motivated by practical applicability and focus on two main challenges faced by practitioners in industry: 1) meaningful formulation of the optimization problem reflecting the needs of a decision maker and 2) finding a desirable solution based on a decision maker's preferences when solving a problem with computationally expensive function evaluations. For the first challenge, we describe the procedure of modelling a component in the air intake ventilation system with commercial simulation tools. The problem to be solved involves time consuming computational fluid dynamics simulations. Therefore, for the second challenge, we extend a recently proposed Kriging-assisted evolutionary algorithm K-RVEA to incorporate a decision maker's preferences. Our numerical results indicate efficiency in using the computing resources available and the solutions obtained reflect the decision maker's preferences well. Actually, two of the solutions dominate the baseline design (the design provided by the decision maker before the optimization process). The decision maker was satisfied with the results and eventually selected one as the final solution.