论文标题
将基于自动混合代理的计算应用于困难的优化问题
Applying Autonomous Hybrid Agent-based Computing to Difficult Optimization Problems
论文作者
论文摘要
进化多代理系统（EMASS）非常擅长处理困难的多维问题，理论上证明了它们的疗效是基于对基于马尔可夫链的模型的分析。现在，研究继续将自动杂交引入EMAS。本文重点介绍了EMA的提议的混合版本，并涵盖了许多混合操作员的选择和介绍，并定义了启动主要算法的混合步骤的规则。这些混合步骤利用现有的，众所周知和被证明是有效的元启发式学，并将其结果整合到主要算法中。根据许多困难的连续优化基准评估了讨论的修改。
Evolutionary multi-agent systems (EMASs) are very good at dealing with difficult, multi-dimensional problems, their efficacy was proven theoretically based on analysis of the relevant Markov-Chain based model. Now the research continues on introducing autonomous hybridization into EMAS. This paper focuses on a proposed hybrid version of the EMAS, and covers selection and introduction of a number of hybrid operators and defining rules for starting the hybrid steps of the main algorithm. Those hybrid steps leverage existing, well-known and proven to be efficient metaheuristics, and integrate their results into the main algorithm. The discussed modifications are evaluated based on a number of difficult continuous-optimization benchmarks.
