Decision Making with Linear Partial Information (L.P.I.)

1984 ◽  
Vol 35 (12) ◽  
pp. 1079 ◽  
Author(s):  
E. Kofler ◽  
Z. W. Kmietowicz ◽  
A. D. Pearman
Keyword(s):  
Decision Making ◽  
Partial Information ◽  
Linear Partial Information

Decision Making with Linear Partial Information (L.P.I.)

1984 ◽  
Vol 35 (12) ◽  
pp. 1079-1090 ◽  
Author(s):  
E. Kofler ◽  
Z. W. Kmietowicz ◽  
A. D. Pearman
Keyword(s):  
Decision Making ◽  
Partial Information ◽  
Linear Partial Information

scholarly journals Interval-Valued Probabilistic Hesitant Fuzzy Set Based Muirhead Mean for Multi-Attribute Group Decision-Making

Mathematics ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 342 ◽  
Author(s):  
Krishankumar ◽  
Ravichandran ◽  
Ahmed ◽  
Kar ◽  
Peng
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Set ◽  
Group Decision ◽  
Partial Information ◽  
Programming Model ◽  
Hesitant Fuzzy Set ◽  
Occurrence Probability ◽  
Source Selection ◽  
Interval Valued

As a powerful generalization to fuzzy set, hesitant fuzzy set (HFS) was introduced, which provided multiple possible membership values to be associated with a specific instance. But HFS did not consider occurrence probability values, and to circumvent the issue, probabilistic HFS (PHFS) was introduced, which associates an occurrence probability value with each hesitant fuzzy element (HFE). Providing such a precise probability value is an open challenge and as a generalization to PHFS, interval-valued PHFS (IVPHFS) was proposed. IVPHFS provided flexibility to decision makers (DMs) by associating a range of values as an occurrence probability for each HFE. To enrich the usefulness of IVPHFS in multi-attribute group decision-making (MAGDM), in this paper, we extend the Muirhead mean (MM) operator to IVPHFS for aggregating preferences. The MM operator is a generalized operator that can effectively capture the interrelationship between multiple attributes. Some properties of the proposed operator are also discussed. Then, a new programming model is proposed for calculating the weights of attributes using DMs’ partial information. Later, a systematic procedure is presented for MAGDM with the proposed operator and the practical use of the operator is demonstrated by using a renewable energy source selection problem. Finally, the strengths and weaknesses of the proposal are discussed in comparison with other methods.

One-shot decisions under Linear Partial Information

1993 ◽  
Vol 34 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Edward Kofler ◽  
Peter Zweifel
Keyword(s):  
Partial Information ◽  
Linear Partial Information

A Simulation-Based Approach to Decision Making with Partial Information

2012 ◽  
Vol 9 (4) ◽  
pp. 329-347 ◽  
Author(s):  
Luis V. Montiel ◽  
J. Eric Bickel
Keyword(s):  
Decision Making ◽  
Partial Information ◽  
Simulation Based

scholarly journals An inexact multi-stage interval-parameter partial information programming model for water resources management under uncertainties

2020 ◽  
Author(s):  
Hongguang Chen ◽  
Zhongjun Wang
Keyword(s):  
Water Resources ◽  
Water Resources Management ◽  
Partial Information ◽  
Programming Model ◽  
Urban Water ◽  
Interval Parameter ◽  
Planning Time ◽  
Resources Management ◽  
Multi Stage ◽  
Linear Partial Information

Abstract The urban water shortage crisis around the world is increasing. In this study, an inexact multi-stage interval-parameter partial information programming model (IMIPM) is proposed for urban water resources planning and management under uncertainties. Optimization techniques of two-stage stochastic programming (TSP), interval-parameter programming (IPP), linear partial information theory (LPI) and multistage stochastic programming (MSP) are combined into one general framework. IMIPM is used to tackle uncertainties like interval numbers, water inflow probabilities expressed as linear partial information, dynamic features in a long planning time and joint probabilities in water resources management. It is applied to Harbin where the manager needs to allocate water from multi-water sources to multi-water users during multi-planning time periods. Four water flow probability scenarios are obtained, which are associated with uncertainties of urban rainfall information. The results show that the dynamics features and uncertainties of system parameters (such as water allocation targets and shortage) are considered in this model by generating a set of representative scenarios within a multistage context. The results also imply that IMIPM can truly reflect the actual urban water resources management situation, and provide managers with decision-making space and technical support to promote the sustainable development of economics and the ecological environment in cities.

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