计算机应用与软件
計算機應用與軟件
계산궤응용여연건
COMPUTER APPLICATIONS AND SOFTWARE
2013年
9期
300-304,308
,共6页
多目标进化算法%引用点方法%邻居支配关系%感兴趣区域%偏好信息
多目標進化算法%引用點方法%鄰居支配關繫%感興趣區域%偏好信息
다목표진화산법%인용점방법%린거지배관계%감흥취구역%편호신식
Multi-objective evolutionary algorithm%Reference point approach%Neighbour dominant relationship%Region of interest%Preference information
传统多目标优化算法得到的解集是整个Pareto最优面，需要花费大量精力在Pareto最优解的搜索上，同时当问题目标个数较多时，决策者很难从大量的解中选出自己最满意的解。因此，针对上述问题，提出一种基于邻居关系的偏好多目标进化算法。该算法通过一个邻居支配关系对非支配个体集进行适应度分层，借助参考点引导个体种群向决策者感兴趣的区域靠近。通过与几种经典的偏好多目标进化算法进行比较实验，结果表明，所提出的算法能引导种群趋近于决策者最满意的区域。
傳統多目標優化算法得到的解集是整箇Pareto最優麵，需要花費大量精力在Pareto最優解的搜索上，同時噹問題目標箇數較多時，決策者很難從大量的解中選齣自己最滿意的解。因此，針對上述問題，提齣一種基于鄰居關繫的偏好多目標進化算法。該算法通過一箇鄰居支配關繫對非支配箇體集進行適應度分層，藉助參攷點引導箇體種群嚮決策者感興趣的區域靠近。通過與幾種經典的偏好多目標進化算法進行比較實驗，結果錶明，所提齣的算法能引導種群趨近于決策者最滿意的區域。
전통다목표우화산법득도적해집시정개Pareto최우면，수요화비대량정력재Pareto최우해적수색상，동시당문제목표개수교다시，결책자흔난종대량적해중선출자기최만의적해。인차，침대상술문제，제출일충기우린거관계적편호다목표진화산법。해산법통과일개린거지배관계대비지배개체집진행괄응도분층，차조삼고점인도개체충군향결책자감흥취적구역고근。통과여궤충경전적편호다목표진화산법진행비교실험，결과표명，소제출적산법능인도충군추근우결책자최만의적구역。
The solutions set gained by traditional multi-objective optimisation algorithms is the entire optimal surface of Pareto , this has to pay much attention to searching the Pareto-optimal solutions .Meanwhile , when the number of objectives for the problem is large , it’ s difficult for the decision maker to choose the most satisfying solution from so many solutions .Therefore, considering the above problems , we propose a neighbour relationship-based preference multi-objective evolutionary algorithm .By stratifying the fitness on the non-dominant individuals set by a neighbour dominant relationship and using the reference point , the algorithm guides the individual population approaching the interested region of the decision maker .According to the comparison experiments with some classical preference multi-objective evolutionary algorithms , the results show that the proposed algorithm can well guide the population closing to the most satisfying areas of the decision makers .
