摘要翻译:
将模糊集理论和模糊逻辑集成到调度中是一个相当新的方面,在制造业的应用中越来越重要,导致了许多尚未解决的问题。在本文中,我们研究了一种改进的局部搜索技术,利用问题的多准则形式来求解具有适应度平台的模糊调度问题。我们特别解决了随着时间的推移而改变工作优先级的问题,这是在舍伍德出版社有限公司进行的研究,舍伍德出版社是一家总部位于诺丁汉的印刷公司,是该项目的合作者。
---
英文标题:
《Improving Local Search for Fuzzy Scheduling Problems》
---
作者:
Martin Josef Geiger, Sanja Petrovic
---
最新提交年份:
2008
---
分类信息:
一级分类:Computer Science 计算机科学
二级分类:Artificial Intelligence 人工智能
分类描述:Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域,除了视觉、机器人、机器学习、多智能体系统以及计算和语言(自然语言处理),这些领域有独立的学科领域。特别地,包括专家系统,定理证明(尽管这可能与计算机科学中的逻辑重叠),知识表示,规划,和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
--
---
英文摘要:
The integration of fuzzy set theory and fuzzy logic into scheduling is a rather new aspect with growing importance for manufacturing applications, resulting in various unsolved aspects. In the current paper, we investigate an improved local search technique for fuzzy scheduling problems with fitness plateaus, using a multi criteria formulation of the problem. We especially address the problem of changing job priorities over time as studied at the Sherwood Press Ltd, a Nottingham based printing company, who is a collaborator on the project.
---
PDF链接:
https://arxiv.org/pdf/0809.0662