A two-stage preference-based evolutionary multi-objective approach for capability planning problems

被引:25
|
作者
Xiong, Jian [1 ,2 ]
Yang, Ke-wei [1 ,3 ]
Liu, Jing [2 ]
Zhao, Qing-song [1 ]
Chen, Ying-wu [1 ]
机构
[1] Natl Univ Def Technol, Coll Informat Syst & Management, Dept Management Sci & Engn, Changsha 410073, Hunan, Peoples R China
[2] Univ New S Wales, Australian Def Force Acad, Sch Engn & Informat Technol, Canberra, ACT 2600, Australia
[3] Univ York, Dept Comp Sci, York YO10 5GH, N Yorkshire, England
基金
中国国家自然科学基金;
关键词
Capability planning problem; Multi-mode resource investment project scheduling; Multi-objective optimization; Preference-based multi-objective evolutionary algorithm; Two-stage approach; PROJECT SCHEDULING PROBLEM; GENETIC ALGORITHM; RESOURCE; OPTIMIZATION; MODELS;
D O I
10.1016/j.knosys.2012.02.003
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
As a type of long-term planning problems, capability planning problems (CPPs) have received considerable attention in the defense and military area. In this paper, we model CPPs as a type of project scheduling problems, referred to as multi-mode resource investment project scheduling problems (MRIPSPs). The makespan and the cost are simultaneously considered. To deliver decision support, a two-stage approach is developed considering both operational and strategic perspectives. At both levels, knowledge of experts or preference of decision makers is utilized. By integrating domain knowledge at the operational level and preference information at the strategic level into the optimization algorithm, a two-stage preference-based multi-objective evolutionary algorithm is proposed. A hypothetical case with 16 tasks is studied. The experimental results show that by focusing computational efforts on the sub-regions where experts or decision makers are interested, we can obtain the solutions which are not only closer to the true Pareto front in objective space, but also hold good characteristics in decision space. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:128 / 139
页数:12
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