摘要
为提高复杂决策环境下产品设计任务规划的科学性,针对设计项目中资源以知识型员工为主的特点,综合考虑项目时间最短、完成质量最高及设计人员负载均衡等问题建立多目标优化的数学模型.在此基础上,为提高横向搜索能力以获得多样性解,提出了基于病毒进化机制的求解算法,其中引入多种群思想以使算法适用于多目标问题,并采用非支配排序保证算法全局搜索能力.最后通过仿真分析对文中算法进行了验证.
To improve efficiency of product design task scheduling in complex decision-making environment, considering knowledge-based designers as resources, a multi-objective optimization model for shortest duration, highest quality and best designer load balancing is build. On this basis, to enhance horizontal search ability for better solutions with diversity, virus evolution-based algorithm is proposed. Multi-group strategy is introduced for solving the multi-objective problem, and nondominated sorting algorithm is used to ensure the global search ability. Finally simulation analysis is performed to validate algorithm effectiveness.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2011年第2期350-356,共7页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(60939003)
国家"八六三"高技术研究发展计划(2009AA043404)
关键词
设计任务规划
多目标优化
病毒进化遗传算法
非支配排序遗传算法Ⅱ
design task scheduling
multi-objective optimization
virus evolution-based genetic algorithm
nondominated sorting genetic algorithmⅡ
