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Learning from the Past to Dynamically Improve Search: A Case Study on the MOSP Problem

机译:从过去学习以动态改善搜索:一个关于MOSP问题的案例研究

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This paper presents a study conducted on the minimum number of open stacks problem (MOSP) which occurs in various production environments where an efficient simultaneous utilization of resources (stacks) is needed to achieve a set of tasks. We investigate through this problem how classical look-back reasonings based on explanations could be used to prune the search space and design a new solving technique. Explanations have often been used to design intelligent backtracking mechanisms in Constraint Programming whereas their use in nogood recording schemes has been less investigated. In this paper, we introduce a generalized nogood (embedding explanation mechanisms) for the MOSP that leads to a new solving technique and can provide explanations.
机译:本文介绍了在各种生产环境中发生的最小开放堆栈问题(MOSP)的研究,其中需要有效地使用资源(堆栈)来实现一组任务。我们通过这个问题调查了基于解释的古典看背面推理来修剪搜索空间并设计一种新的求解技术。解释通常用于设计约束编程中的智能回溯机制,而它们在Nogood录制方案中的使用较少。在本文中,我们向MOSS介绍了一个通用的Nogood(嵌入说明机制),以导致新的解决技术,并可以提供解释。

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