scholarly journals A New Application for the Goal Programming—The Target Decision Rule for Uncertain Problems

2020 ◽  
Vol 13 (11) ◽  
pp. 280
Author(s):  
Helena Gaspars-Wieloch
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Decision Rule ◽  
Goal Programming ◽  
The Other ◽  
Decision Making Under Uncertainty ◽  
Multi Criteria Decision Making ◽  
Other Hand ◽  
Novel Method

The goal programming (GP) is a well-known approach applied to multi-criteria decision making (M-DM). It has been used in many domains and the literature offers diverse extensions of this procedure. On the other hand, so far, some evident analogies between M-DM under certainty and scenario-based one-criterion decision making under uncertainty (1-DMU) have not been revealed in the literature. These similarities give the possibility to adjust the goal programming to an entirely new domain. The purpose of the paper is to create a novel method for uncertain problems on the basis of the GP ideas. In order to achieve this aim we carefully examine the analogies occurring between the structures of both issues (M-DM and 1-DMU). We also analyze some differences resulting from a different interpretation of the data. By analogy to the goal programming, four hybrids for 1-DMU are formulated. They differ from each other in terms of the type of the decision maker considered (pessimist, optimist, moderate). The new decision rule may be helpful when solving uncertain problems since it is especially designed for neutral criteria, which are not taken into account in existing procedures developed for 1-DMU.

scholarly journals From Goal Programming for Continuous Multi-Criteria Optimization to the Target Decision Rule for Mixed Uncertain Problems

Entropy ◽  
2021 ◽  
Vol 24 (1) ◽  
pp. 51
Author(s):  
Helena Gaspars-Wieloch
Keyword(s):  
Decision Making ◽  
Decision Rule ◽  
Goal Programming ◽  
Decision Makers ◽  
Decision Making Under Uncertainty ◽  
Multi Criteria Decision Making ◽  
The Novel ◽  
Continuous Version ◽  
Novel Approach

Goal programming (GP) is applied to the discrete and continuous version of multi-criteria optimization. Recently, some essential analogies between multi-criteria decision making under certainty (M-DMC) and scenario-based one-criterion decision making under uncertainty (1-DMU) have been revealed in the literature. The aforementioned similarities allow the adjustment of GP to an entirely new domain. The aim of the paper is to create a new decision rule for mixed uncertain problems on the basis of the GP methodology. The procedure can be used by pessimists, optimists and moderate decision makers. It is designed for one-shot decisions. One of the significant advantages of the novel approach is related to the possibility to analyze neutral criteria, which are not directly taken into account in existing classical procedures developed for 1-DMU.

scholarly journals On some analogies between one-criterion decision making under uncertainty and multi-criteria decision making under certainty

2021 ◽  
Vol 7 (2) ◽  
pp. 17-36
Author(s):  
Helena Gaspars-Wieloch
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Scenario Planning ◽  
Decision Problems ◽  
Careful Examination ◽  
Decision Making Under Uncertainty ◽  
Multi Criteria Decision Making ◽  
Novel Approaches ◽  
Uncertain Future ◽  
New Algorithms

One-criterion decision making under uncertainty (1-DM/U) is related to situations in which the decision maker (DM) evaluates the alternatives on the basis of one objective, but e.g. due to numerous uncertain future factors some parameters of the problem are not deterministic. Instead of entirely known paramaters, a set of possible scenarios is available. Multi-criteria decision making under certainty (M-DM/C) concerns cases where the DM assesses particular options in terms of many objectives. The parameters are known. Therefore, scenario planning is redundant. Both issues are investigated by many researchers and practitioners, since real economic decision problems are usually at least uncertain or multi-objective. In the paper, numerous analogies between 1-DM/U and M-DM/C are revealed. Some of them have existed for many decades, but others, so far, have not been developed. A careful examination of all the similarities enables an improvement of existing methods and a formulation of new algorithms for 1-DM/U and M-DM/C. The article presents six pairs of similar procedures and contains the description of three novel approaches created by analogy to existing ones.

scholarly journals Measuring and Comparing Two Kinds of Rationalizable Opportunity Cost in Mixture Models

Games ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 1
Author(s):  
James R. Bland
Keyword(s):  
Decision Making ◽  
Mixture Models ◽  
Decision Maker ◽  
Opportunity Cost ◽  
The Other ◽  
Choice Rule ◽  
Decision Making Under Risk ◽  
Probabilistic Choice ◽  
Other Hand

In experiments of decision-making under risk, structural mixture models allow us to take a menu of theories about decision-making to the data, estimating the fraction of people who behave according to each model. While studies using mixture models typically focus only on how prevalent each of these theories is in people’s decisions, they can also be used to assess how much better this menu of theories organizes people’s utility than does just one theory on its own. I develop a framework for calculating and comparing two kinds of rationalizable opportunity cost from these mixture models. The first is associated with model mis-classification: How much worse off is a decision-maker if they are forced to behave according to model A, when they are in fact a model B type? The second relates to the mixture model’s probabilistic choice rule: How much worse off are subjects because they make probabilistic, rather than deterministic, choices? If the first quantity dominates, then one can conclude that model a constitutes an economically significant departure from model B in the utility domain. On the other hand, if the second cost dominates, then models a and B have similar utility implications. I demonstrate this framework on data from an existing experiment on decision-making under risk.

scholarly journals Applicability of Artificial Intelligence in Decision-Making for Land Forces

2021 ◽  
Vol 30 (2) ◽  
pp. 039-054
Author(s):  
Paul Tudorache
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Research Methodology ◽  
Research Paper ◽  
The Other ◽  
Military Operations ◽  
Other Hand ◽  
The Military

Similar to other fields, also in the military one, the Artificial Intelligence has become recently an evident solution for optimizing specific processes and activities. Therefore, this research paper aims to highlight the potential uses of Artificial Intelligence in the military operations carried out by the Land Forces. In this regard, analysing the framework of the operations process and applying suitable research methodology, the main findings are related to AI’s contributions in optimizing commander’s decisions during the progress of planning and execution. On the other hand, picturing the AI upgrated combat power of the Land Forces is another significant result of this study.

Rationality and Consensus in Kwasi Wiredu’s Traditional African Polities

Theoria ◽  
2016 ◽  
Vol 63 (146) ◽  
pp. 36-55
Author(s):  
Bernard Matolino
Keyword(s):  
Decision Making ◽  
Crucial Role ◽  
Modern Society ◽  
The Other ◽  
Rational Persuasion ◽  
Other Hand

Abstract The disagreement over what was responsible for arriving at consensual positions, in traditional African polities, is best captured in the classic debate between Kwasi Wiredu and Emmanuel Eze. The former holds that rational persuasion was the sole informant of decision-making while the latter argues that non-rational factors played a crucial role in securing a consensual decision. If Wiredu is correct then consensus could work in modern society as it can be argued that it does not rely on traditionalistic scaffoldings. If, on the other hand, Eze is correct, then consensus cannot work in modern largely urbanised Africa as its traditional underpinnings have largely disappeared. While Emmanuel Ani’s intervention in this debate is welcome for its earnest search for a system that could work, his support for Eze is not bold enough to undermine Wiredu’s rationalistic orientation in consensus.

New Einstein Hybrid Aggregation Operators for Intuitionistic Fuzzy Sets and Applications in Multi-Criteria Decision-Making

2019 ◽  
pp. 252-283
Author(s):  
Bhagawati Prasad Joshi ◽  
Abhay Kumar
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Decision Maker ◽  
Intuitionistic Fuzzy Sets ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Multi Criteria Decision Making ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Decision Making Processes

The fusion of multidimensional intuitionistic fuzzy information plays an important part in decision making processes under an intuitionistic fuzzy environment. In this chapter, it is observed that existing intuitionistic fuzzy Einstein hybrid aggregation operators do not follow the idempotency and boundedness. This leads to sometimes illogical and even absurd results to the decision maker. Hence, some new intuitionistic fuzzy Einstein hybrid aggregation operators such as the new intuitionistic fuzzy Einstein hybrid weighted averaging (IFEHWA) and the new intuitionistic fuzzy Einstein hybrid weighted geometric (IFEHWG) were developed. The new IFEHWA and IFEHWG operators can weigh the arguments as well as their ordered positions the same as the intuitionistic fuzzy Einstein hybrid aggregation operators do. Further, it is validated that the defined operators are idempotent, bounded, monotonic and commutative. Then, based on the developed approach, a multi-criteria decision-making (MCDM) procedure is given. Finally, a numerical example is conducted to demonstrate the proposed method effectively.

Goal Programming and Its Variants

2011 ◽  
pp. 410-417
Author(s):  
John Wang ◽  
Dajin Wang ◽  
Aihua Li
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Goal Programming ◽  
Multicriteria Decision Making ◽  
Industrial Applications ◽  
Multiple Objective ◽  
Multi Criteria Decision Making ◽  
Powerful Method ◽  
Noticeable Increase ◽  
New Type

Within the realm of multicriteria decision making (MCDM) exists a powerful method for solving problems with multiple objectives. Goal programming (GP) was the first multiple-objective technique presented in the literature (Dowlatshahi, 2001). The premise of GP traces its origin back to a linear programming study on executive compensation in 1955 by Charnes, Cooper, and Ferguson even though the specific name did not appear in publications until the 1961 textbook entitled Management Models and Industrial Applications of Linear Programming, also by Charnes and Cooper (Schniederjans, 1995). Initial applications of this new type of modeling technique demonstrated its potential for a variety of applications in numerous different areas. Until the middle of the 1970s, GP applications reported in the literature were few and far between. Since that time, primarily due to influential works by Lee and Ignizio, a noticeable increase of published GP applications and technical improvements has been recognized. The number of case studies, along with the range of fields, to which GP has been and still is being applied is impressive, as shown in surveys by Romero (1991) and Aouni and Kettani (2001). It can be said that GP has been, and still is, the “most widely used multi-criteria decision making technique” (Tamiz, Jones, & Romero, 1998, p. 570).

Goal Programming for Decision Making in Closely Held Businesses

1979 ◽  
Vol 3 (4) ◽  
pp. 31-41 ◽  
Author(s):  
Sang M. Lee ◽  
Robert T. Justis ◽  
Lori Sharp Franz
Keyword(s):  
Decision Making ◽  
Small Business ◽  
Decision Maker ◽  
Goal Programming ◽  
Small Businesses ◽  
Fast Food ◽  
Programming Model ◽  
Multiple Goals ◽  
Business Decision ◽  
Goal Programming Model

There are few analytical and managerial tools available to assist the small business decision maker. This paper presents a practical goal Programming model which can be easily generalized to fit the planning needs of most small businesses. Specifically the model explicitly considers the multiple goals and priorities of the owner-manager and determines if these goals can be accomplished under various demand Projections. An illustrative example of the use of this model with a small fast-food business is given.

Sign in / Sign up

Export Citation Format

Share Document