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路红,张莉,岳涛.面向产品线交互配置不一致性修复的差分IBEA算法.软件学报,2016,27(4):901-915
面向产品线交互配置不一致性修复的差分IBEA算法
Differential IBEA for Non-Conformity Resolution in Interactive CPS Production Line Configuration
投稿时间:2015-08-31  修订日期:2015-10-15
DOI:10.13328/j.cnki.jos.004969
中文关键词:  信息物理系统产品线  一致性检查  不一致修复  基于搜索的软件工程  多目标搜索  约束求解
英文关键词:CPS product line  conformance checking  nonconformity resolving  search based software engineering  multi-objective search  constraint solving
基金项目:国家自然科学基金(61370058,61170087)
作者单位E-mail
路红 北京航空航天大学 计算机学院, 北京 100191  
张莉 北京航空航天大学 计算机学院, 北京 100191 lily@buaa.edu.cn 
岳涛 Simula Research Laboratory & University of Oslo, Oslo 1325, Norway  
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全文下载次数: 1217
中文摘要:
      在大规模复杂系统产品线工程中,人工配置难免会导致配置的不一致,即,配置数据会违背预定义的约束(也可以称为一致性约束).对于大规模复杂系统产品线体系结构,比如信息物理系统产品线,往往存在成百上千的可变点以及约束,而且约束与可变点之间存在复杂的依赖关系,为不一致配置的修复带来很大的挑战.为了解决这个问题,针对前期提出的基于多目标搜索以及约束求解技术的自动不一致配置修复推荐框架(Zen-Fix),提出一种改进的IBEA算法(DeIBEA).DeIBEA通过将差分引入IBEA算法,搜索过程中,基于可行解和不可行解的差分变异产生后代,最终为用户推荐符合预定义约束并且对于配置效率来说最优的配置修复方案.基于一个工业案例海底油田采控系统产品线为例,通过模拟一个产品的配置过程,产生了10189个优化问题,结果表明:Zen-Fix框架结合DeIBEA算法,可以实时地为用户提供较优的不一致配置修复方案.此外,通过对这10189个问题的推荐方案进行对比,证明了DeIBEA算法无论从时间效率还是搜索性能上都优于原始的IBEA算法.
英文摘要:
      In large system production line configuration, manual configuration is inevitable and hence easy to introduce nonconformities where configuration data inputted by configuration engineers violate predefined constraints(also known as conformance constraints). For large system production lines, such as cyber physical system(CPS) product lines, there are usually hundreds and thousands of configurable parameters, hundreds of conformance constraints, and complicated dependencies among the conformance constraints. Thus it is very challenging to resolve nonconformities in an efficient manner. As a first step to address this challenge, an automated nonconformity resolving recommendation approach(Zen-Fix) was presented in the previous work by this research, which relies on multi-objective search and constraint solving techniques. To further improve the search efficiency in such interactive CPS configuration process, this paper proposes a novel algorithm called DeIBEA, which combines differential evolution with IBEA(indicator-based evolutionary algorithm), and distinguishes feasible solutions from infeasible ones, generating offspring through the differential operation. Integrating Zen-Fix with DeIBEA can recommend nonconformity-free yet optimal solutions to configuration engineers. The cost effectiveness of DeIBEA(in the context of Zen-Fix) is empirically evaluated with a real-world case study, in which a configuration process is simulated containing 10189 search problems. Results show that:(1) Zen-Fix with DeIBEA can provide nonconformity resolving recommendation automatically in a quite efficient way;(2) Compared with IBEA, DeIBEA performs significantly better in terms of both time performance and search performance.
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