摘要翻译：
本文提出了一种新的多目标混合模型，使禁忌搜索(TS)所提供的邻域方法的研究能力与进化算法的重要探索能力相结合。使用计算机网络，在基准函数(ZDT1、ZDT2和ZDT3)中实现并测试了该模型。
---
英文标题：
《Hybrid Model for Solving Multi-Objective Problems Using Evolutionary
  Algorithm and Tabu Search》
---
作者：
Rjab Hajlaoui, Mariem Gzara, Abdelaziz Dammak
---
最新提交年份：
2011
---
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：
  This paper presents a new multi-objective hybrid model that makes cooperation between the strength of research of neighborhood methods presented by the tabu search (TS) and the important exploration capacity of evolutionary algorithm. This model was implemented and tested in benchmark functions (ZDT1, ZDT2, and ZDT3), using a network of computers.
---
PDF链接：
https://arxiv.org/pdf/1102.2984