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Optimizing User Guidance during Decision-Making

机译:在决策过程中优化用户指导

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The configuration of a product from a product line is a decision-making process that requires humans to answer questions. However, questions and their choices tend to affect one another (e. g., one feature depending on another) and decisions on how questions are answered may render other questions obsolete or reduce their choices. There is thus an ideal order in which questions should be answered to minimize the number of questions that need answering to completely configure a product. Unfortunately, this ideal order differs depending on the product -- which cannot be known a priori. Decision-making is thus characterized by either imposing a predefined order on how questions must be answered (usually done manually by product line engineers) or not imposing any order. Both situations have downsides and this paper thus proposes an alternative: an incremental algorithm and tool-support for automatically optimizing the order of questions with every answer. We evaluated our approach on six models, the largest with over 280 questions, and found that the approach is 78-99% optimal and significantly reduces the number of questions that need to be answered manually. For the creators of product line models, this implies savings in not having to predefine the optimal order which is exponentially complex. For the configurator (decision maker) this implies more freedom in the order in which to answer questions while still benefiting from guidance.
机译:生产线中产品的配置是一个决策过程,需要人工回答问题。然而,问题及其选择趋于彼此影响(例如,一个特征取决于另一特征),并且关于如何回答问题的决定可能使其他问题过时或减少其选择。因此,存在一个理想的顺序,在该顺序中,应该回答问题以最小化为完全配置产品而需要回答的问题数量。不幸的是,这种理想的订单因产品而异-不能事先知道。因此,决策的特征是对问题的回答方式施加了预定的顺序(通常由产品线工程师手动完成)或不施加任何顺序。两种情况都有缺点,因此本文提出了一种替代方案:一种增量算法和工具支持,用于自动优化每个答案的问题顺序。我们在六个模型上评估了我们的方法,最大的模型有280多个问题,发现该方法是78-99%的最优方法,可显着减少需要手动回答的问题数量。对于产品线模型的创建者而言,这意味着无需预先定义成倍复杂的最优订单即可节省成本。对于配置者(决策者)而言,这意味着在回答问题的同时可以享受更多自由,同时仍然可以从指导中受益。

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