MULTIOBJECTIVE WATER-RESOURCES INVESTMENT PLANNING UNDER BUDGETARY UNCERTAINTY AND FUZZY ENVIRONMENT

被引:10
|
作者
SUTARDI
BECTOR, CR
GOULTER, I
机构
[1] UNIV MANITOBA,DEPT ACTUARIAL & MANAGEMENT SCI,WINNIPEG,MB R3T 5V4,CANADA
[2] UNIV CENT QUEENSLAND,ROCKHAMPTON,QLD 4702,AUSTRALIA
[3] MINIST PUBL WORKS,DIRECTORATE GEN WATER RESOURCES DEV,JAKARTA,INDONESIA
关键词
PLANNING; STOCHASTIC; DYNAMIC; GOAL; FUZZY;
D O I
10.1016/0377-2217(93)E0332-R
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
An integration of Stochastic Dynamic Programming (SDP) and Fuzzy Integer Goal Programming (FIGP) modelling framework is proposed to handle problems of multiobjective-multicriteria sequential decision making under budgetary and socio-technical uncertainties inherent in water resources investment planning. In the proposed SDP model probabilities of the funding levels in any time period that are generated using a subjective model are employed to handle budgetary fluctuations. This subjective model consists of historical data as a basic rate, functional relationships among inter-related parameters of the SDP model, scenarios of future budget availability, and subjective inputs elicited from a group of decision makers through a collective opinion technique. Use of the SDP model primarily yields an optimal investment planning policy that recognizes the possibility that actual funding received maybe less than the anticipated and therefore the projects being implemented under the anticipated budget would be interrupted. Economic return of each level of investment decision together with its associated project portfolio is determined by the FIGP model under the environment of imprecise (fuzzy) budget limits and goals, and is then used in the SDP model to establish the sequential optimal policy. This second level optimization model can be used to handle other types of socio-economic uncertainty and multiobjective issues in the overall approach by considering explicitly socio-economic measures and imprecision in the specification of parameters of input data.
引用
收藏
页码:556 / 591
页数:36
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