摘要
为了克服传统的基于任务优先规则的启发式算法的局限性,提高并行工程项目的资源配置效率和缩短项目工期,提出了一种基于串行进度生成机制的组合随机抽样算法.该算法拓展了单项目串行进度生成机制,并引入基于后悔值的随机函数,组合不同的任务优先规则,对并行项目的各任务进行重复随机抽样,从而选择最好的进度计划.经系统算例检验表明,该算法能够有效优化并行项目的资源配置,从而显著缩短项目工期.
In order to overcome the shortcoming of traditional priority rule based heuristics, a new composite random sampling method based on serial schedule generation scheme was proposed to increase the effectiveness of resource allocation and shorten the overall project durations. The method extends the serial schedule generation scheme used in single project scheduling to multi-project scheduling problems. Using the regret-based biased random sampling technique, the method combines various priority rules to schedule a set of simultaneous projects repetitively, so as to select the best multi-project schedule. Systematic experimental tests show that the proposed composite random sampling method improves the resource allocation among project activities and significantly shortens the overall project durations.
出处
《浙江大学学报（工学版）》
EI
CAS
CSCD
北大核心
2006年第2期344-347,共4页
Journal of Zhejiang University：Engineering Science
基金
国家自然科学基金资助项目(70401017)
关键词
项目调度
资源约束
随机抽样
project scheduling
resource constraint
random sampling
