Optimal product design using a colony of virtual ants
Optimal product design using a colony of virtual ants
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DOI：
10.1016/j.ejor.2005.06.042
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
M. Albritton;P. McMullen
中科院分区：
文献类型：
--
作者：
M. Albritton;P. McMullen
最优产品设计问题，即“最佳”产品功能组合被制定为理想的产品，是使用蚁群优化 (ACO) 来制定的。在这里，基于社交昆虫行为的算法被应用于消费者决策模型，该模型旨在指导新产品决策并允许规划和评估产品提供场景。 ACO 启发式方法可以有效地搜索巨大的决策空间，并且在模型输入不断变化时非常灵活。与完全枚举所有可能的解决方案相比，ACO 可以为该问题生成接近最佳的结果。先前的研究主要集中于使用单个时间点的消费者偏好数据进行最佳产品规划。现有文献表明，这些表述过于简单化，因为消费者对产品的偏好程度受到过去经验和先前选择的影响。该应用程序将消费者偏好建模为随着时间的推移而不断变化的演变。
The optimal product design problem, where the “best” mix of product features are formulated into an ideal offering, is formulated using ant colony optimization (ACO). Here, algorithms based on the behavior of social insects are applied to a consumer decision model designed to guide new product decisions and to allow planning and evaluation of product offering scenarios. ACO heuristics are efficient at searching through a vast decision space and are extremely flexible when model inputs continuously change. When compared to complete enumeration of all possible solutions, ACO is found to generate near-optimal results for this problem. Prior research has focused primarily on optimal product planning using consumer preference data from a single point in time. Extant literature suggests these formulations are overly simplistic, as a consumer’s level of preference for a product is affected by past experience and prior choices. This application models consumer preferences as evolutionary, shifting over time.