大局中的反事实解释:流程预测驱动的作业车间调度优化方法

IF 4.3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
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引用次数: 0

摘要

在本研究中,我们提出了一个开创性的框架,将预测性流程监控与先进的数学优化技术相结合,用于生成作业车间调度背景下的多目标反事实解释。利用非支配排序遗传算法 II(NSGA-II)进行多目标优化,我们的方法增强了反事实解释的生成,从而揭示了操作和系统层面的潜在改进。经过真实世界数据的验证,我们的方法强调了 NSGA-II 在制作中肯、可操作的反事实解释方面的优越性,在效率和实用性方面都超越了传统方法。这项工作推动了可解释人工智能(XAI)、预测过程监控和组合优化领域的发展,为提高自动调度系统的清晰度和决策能力提供了有效工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Counterfactual Explanations in the Big Picture: An Approach for Process Prediction-Driven Job-Shop Scheduling Optimization

Counterfactual Explanations in the Big Picture: An Approach for Process Prediction-Driven Job-Shop Scheduling Optimization

In this study, we propose a pioneering framework for generating multi-objective counterfactual explanations in job-shop scheduling contexts, combining predictive process monitoring with advanced mathematical optimization techniques. Using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) for multi-objective optimization, our approach enhances the generation of counterfactual explanations that illuminate potential enhancements at both the operational and systemic levels. Validated with real-world data, our methodology underscores the superiority of NSGA-II in crafting pertinent and actionable counterfactual explanations, surpassing traditional methods in both efficiency and practical relevance. This work advances the domains of explainable artificial intelligence (XAI), predictive process monitoring, and combinatorial optimization, providing an effective tool for improving automated scheduling systems’ clarity, and decision-making capabilities.

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来源期刊
Cognitive Computation
Cognitive Computation COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-NEUROSCIENCES
CiteScore
9.30
自引率
3.70%
发文量
116
审稿时长
>12 weeks
期刊介绍: Cognitive Computation is an international, peer-reviewed, interdisciplinary journal that publishes cutting-edge articles describing original basic and applied work involving biologically-inspired computational accounts of all aspects of natural and artificial cognitive systems. It provides a new platform for the dissemination of research, current practices and future trends in the emerging discipline of cognitive computation that bridges the gap between life sciences, social sciences, engineering, physical and mathematical sciences, and humanities.
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