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

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.

[1]  Abraham Charnes,et al.  Optimal Estimation of Executive Compensation by Linear Programming , 1955 .

[2]  I. Durbach Outranking under uncertainty using scenarios , 2014, Eur. J. Oper. Res..

[3]  H. Bleichrodt Reference-dependent utility with shifting reference points and incomplete preferences , 2007 .

[4]  James H. Lambert,et al.  Evaluating deep uncertainties in strategic priority‐setting with an application to facility energy investments , 2012, Syst. Eng..

[5]  Mehdi Abapour,et al.  Goal Programming Application for Contract Pricing of Electric Vehicle Aggregator in Join Day-Ahead Market , 2020, Energies.

[6]  Eman Ismail,et al.  A generalized goal programming model for parsimonious robust clusterwise linear regression , 2019 .

[7]  D Giokas The use of goal programming and data envelopment analysis for estimating efficient marginal costs of outputs , 1997 .

[8]  Helena Gaspars-Wieloch,et al.  Project Net Present Value estimation under uncertainty , 2019, Central Eur. J. Oper. Res..

[9]  Matthew J. Liberatore,et al.  Project Planning under Uncertainty Using Scenario Analysis , 2005 .

[10]  H. Tamura,et al.  Goal programming in econometrics , 1970 .

[11]  Helena Gaspars-Wieloch Newsvendor problem under complete uncertainty: a case of innovative products , 2017, Central Eur. J. Oper. Res..

[12]  A. Tversky,et al.  Advances in prospect theory: Cumulative representation of uncertainty , 1992 .

[13]  Tamer Eren,et al.  Scheduling and Planning in Service Systems with Goal Programming: Literature Review , 2018, Mathematics.

[14]  Zubair Ashraf,et al.  Fuzzy Goal Programming with an Imprecise Intuitionistic Fuzzy Preference Relations , 2020, Symmetry.

[15]  Helena Gaspars-Wieloch,et al.  The Impact of the Structure of the Payoff Matrix on the Final Decision made Under Uncertainty , 2018, Asia Pac. J. Oper. Res..

[16]  Helena Gaspars-Wieloch,et al.  The Use of a Modification of the Hurwicz’s Decision Rule in Multicriteria Decision Making under Complete Uncertainty , 2014 .

[17]  Armin Fügenschuh,et al.  Goal Programming Models with Linear and Exponential Fuzzy Preference Relations , 2020, Symmetry.

[18]  Helena Gaspars-Wieloch,et al.  Innovative projects scheduling with scenario-based decision project graphs , 2017 .

[19]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .

[20]  Helena Gaspars-Wieloch,et al.  On a Decision Rule for Mixed Strategy Searching Under Uncertainty on the basis of the Coefficient of Optimism , 2014 .

[21]  Takashi Hayashi,et al.  Regret aversion and opportunity dependence , 2008, J. Econ. Theory.

[22]  Theodor J. Stewart,et al.  Integrating multicriteria decision analysis and scenario planning—Review and extension , 2013 .

[23]  Hao Wen Lin,et al.  An interactive meta-goal programming-based decision analysis methodology to support collaborative manufacturing , 2009 .

[24]  P. Schoemaker Scenario Planning: A Tool for Strategic Thinking , 1995 .

[25]  Alan Schwartz,et al.  Prospect theory, reference points, and health decisions , 2008, Judgment and Decision Making.

[26]  Jerzy Michnik,et al.  Scenario Planning + MCDA Procedure For Innovation Selection Problem , 2013 .

[27]  Helena Gaspars-Wieloch,et al.  Modifications of the Hurwicz’s decision rule , 2014, Central Eur. J. Oper. Res..

[28]  Armin Fügenschuh,et al.  A Multi-Criteria Goal Programming Model to Analyze the Sustainable Goals of India , 2018 .

[29]  Matteo Rocca,et al.  Light Robust Goal Programming , 2019 .

[30]  Helena Gaspars-Wieloch Modifications of the Omega ratio for decision making under uncertainty , 2015 .

[31]  Helena Gaspars-Wieloch On a decision rule supported by a forecasting stage based on the decision maker’s coefficient of optimism , 2015, Central Eur. J. Oper. Res..

[32]  Helena Gaspars-Wieloch,et al.  A decision rule based on goal programming and one-stage models for uncertain multi-criteria mixed decision making and games against nature , 2017 .

[33]  A. Cherepovitsyn,et al.  Methods and Tools of Scenario Planning in Areas of Natural Resources Management , 2018 .

[34]  Liang Liang,et al.  Multiple Attribute Decision Making Based on Cross-Evaluation with Uncertain Decision Parameters , 2016 .

[35]  Guido Reger,et al.  Advantages and Disadvantages of Scenario Approaches for Strategic Foresight , 2005 .

[36]  Aparna Mehra,et al.  Matrix games with 2-tuple linguistic information , 2018, Annals of Operations Research.