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摘要翻译：
双目标IRP的求解是相当具有挑战性的，即使对元启发式也是如此。我们仍然缺乏对适当的解表示和有效的邻域结构的深刻理解。显然，替代品的交付量和路由方面都需要反映在编码中，并且在通过本地搜索进行搜索时必须进行修改。我们的工作有助于更好地理解这样的解决方案表示。在实验研究的基础上，研究和比较了两种编码方式的优缺点。
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英文标题：
《Solution Representations and Local Search for the bi-objective Inventory
Routing Problem》
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作者：
Thibaut Barth\'elemy, Martin Josef Geiger, Marc Sevaux
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最新提交年份：
2012
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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。
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英文摘要：
The solution of the biobjective IRP is rather challenging, even for metaheuristics. We are still lacking a profound understanding of appropriate solution representations and effective neighborhood structures. Clearly, both the delivery volumes and the routing aspects of the alternatives need to be reflected in an encoding, and must be modified when searching by means of local search. Our work contributes to the better understanding of such solution representations. On the basis of an experimental investigation, the advantages and drawbacks of two encodings are studied and compared.
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PDF链接：
https://arxiv.org/pdf/1204.4051
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