系统工程理论与实践
繫統工程理論與實踐
계통공정이론여실천
Systems Engineering—Theory & Practice
2014年
11期
2885~2891
,共null页
鲁棒解 结构元 模糊线性规划 模糊数
魯棒解 結構元 模糊線性規劃 模糊數
로봉해 결구원 모호선성규화 모호수
robust solutions; structured element; fuzzy linear programming; fuzzy number
对于不确定系统的优化问题,模糊线性规划是一种常用的建模方法,但得到的最优解或满意解,往往对参数的变动缺少“免疫”能力,即参数受到扰动后,最初的最优解会变得不再最优甚至不可行.首先针对λ-截集水平下的模糊线性规划,给出了λ-鲁棒解的定义.利用模糊结构元理论对λ-鲁棒解的定义进行表示,得到了求解模型.由于决策者的不同,对解的可实现程度要求不同.故在模型中加入了能够反映决策者风险偏好的测度约束,该模型的解即为γ-鲁棒解,该解既有鲁棒性、优化性,又能体现决策者的风险偏好程度.通过算例可以看出,γ-鲁棒解对参数的变动具有“免疫”能力,能为决策者提供更为丰富的信息,体现出了更好的实用价值.
對于不確定繫統的優化問題,模糊線性規劃是一種常用的建模方法,但得到的最優解或滿意解,往往對參數的變動缺少“免疫”能力,即參數受到擾動後,最初的最優解會變得不再最優甚至不可行.首先針對λ-截集水平下的模糊線性規劃,給齣瞭λ-魯棒解的定義.利用模糊結構元理論對λ-魯棒解的定義進行錶示,得到瞭求解模型.由于決策者的不同,對解的可實現程度要求不同.故在模型中加入瞭能夠反映決策者風險偏好的測度約束,該模型的解即為γ-魯棒解,該解既有魯棒性、優化性,又能體現決策者的風險偏好程度.通過算例可以看齣,γ-魯棒解對參數的變動具有“免疫”能力,能為決策者提供更為豐富的信息,體現齣瞭更好的實用價值.
대우불학정계통적우화문제,모호선성규화시일충상용적건모방법,단득도적최우해혹만의해,왕왕대삼수적변동결소“면역”능력,즉삼수수도우동후,최초적최우해회변득불재최우심지불가행.수선침대λ-절집수평하적모호선성규화,급출료λ-로봉해적정의.이용모호결구원이론대λ-로봉해적정의진행표시,득도료구해모형.유우결책자적불동,대해적가실현정도요구불동.고재모형중가입료능구반영결책자풍험편호적측도약속,해모형적해즉위γ-로봉해,해해기유로봉성、우화성,우능체현결책자적풍험편호정도.통과산례가이간출,γ-로봉해대삼수적변동구유“면역”능력,능위결책자제공경위봉부적신식,체현출료경호적실용개치.
Fuzzy linear programming is used widedly for the problems of uncertain system's optimization, but the optimization solutions or satisfactory solution are often not "immune" to parameters, that is if the parameters are changed, initial optimal solution is no longer optimal or even infeasible. First of all, for the λ-cut level of fuzzy linear programming, λ-robust optimization solutions are put forward; then article indicates the definition of λ-robust solution by fuzzy structured element, and obtains the solving model. Solution can achieve the degree requirements are different due to the different decision makers, therefore, the measure constraints which can reflect the decision-makers risk preferences are added to the model, the solution of this model is γ-robust solution, and the solution not only has the robustness and optimization, but also reflects the degree of risk preference of the decision makers. By an example, it is found that the optimization robust solutions with measurement are immune to parameters, which are more useful for decision-makers and reflect a better practical value.