Journal Article10.1016/J.OMEGA.2005.07.009
Multi-choice goal programming
309
TL;DR: This paper proposes a new idea for programming the MCAL problem, which allows decision-makers to set multiple aspiration levels for their problems in which "the more/higher is better" and "the less/lower is better in the aspiration levels are addressed.
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Abstract: The situation of multi-choice aspiration levels (MCAL) may exist in many decision/management problems. However, the problem cannot be solved by current goal programming (GP) techniques. In order to improve the utility of GP and solve the MCAL problem, this paper proposes a new idea for programming the MCAL problem. The proposed method allows decision-makers (DMs) to set multiple aspiration levels for their problems in which “the more/higher is better” and “the less/lower is better” in the aspiration levels are addressed. In addition, illustrative examples are given to demonstrate the correctness of the proposed model.
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References
Fuzzy programming and linear programming with several objective functions
TL;DR: It is shown that solutions obtained by fuzzy linear programming are always efficient solutions and the consequences of using different ways of combining individual objective functions in order to determine an “optimal” compromise solution are shown.
3.6K
Linear programming with multiple objective functions: Step method (stem)
TL;DR: In this man-model symbiosis, phases of computation alternate with phases of decision, which allows the decision-maker to “learn” to recognize good solutions and the relative importance of the objectives.
954
Variable risk preferences and the focus of attention
James G. March,Zur Shapira +1 more
TL;DR: In this paper, several non-stationary random-walk models of risk taking are developed to describe the phenomenon of individual or organizational risk taking, and the models portray a risk taker's history as the cumulated realizations of a series of independent draws from a normal probability distribution of possible outcomes.
728
Goal programming for decision making: an overview of the current state-of-the-art
TL;DR: Modelling techniques such as detection and restoration of pareto efficiency, normalisation, redundancy checking, and non-standard utility function modelling are overviewed, and the rationality of ranking Multi-Criteria Decision Making techniques is discussed.
691