A framework for multiresolution optimization in a parallel distributed environment: Simulation of hierarchical GAs

作     者：Kim, JW Zeigler, BP 

作者机构：AI and Simulation Group Department of Electrical and Computer Engineering University of Arizona Tucson Arizona 85721 

出 版 物：《JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING》 (并行与分布式计算杂志)

年 卷 期：1996年第32卷第1期

页      面：90-102页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Science Foundation  NSF  (ASC-9318169) 

主　　题：Variable structure PROTOTYPE Gases simulating PAGR1 gene Simulated Environment Agents Searches GALNS gene Clusters Environments 

摘      要：A novel framework for multi-resolution optimization methodology is developed for parallel/distributed simulation environments. The architecture is constructed with multiple clusters hierarchically arranged with each level solving different degrees of abstracted problems. Creation and deletion of clusters are executed dynamically during the search operation. A higher level cluster evaluates a wider search space with low resolution, whereas a lower level cluster investigates a smaller search space which is more promising for containing the global optimum. Each cluster consists of a controller (expert system) and agents (GA), where the agents evaluate the parameters of the problem of variable structure which allocates more computing resources to promising search subspaces. This article describes the prototyping of the hierarchical distributed genetic algorithms (HDGA) in an object-oriented simulation environment and provides preliminary experimental results. The results are promising, and many theoretical questions concerning robustness of the approach are raised for future research. (C) 1996 Academic Press, Inc.