A New Compromise Solution Model Based on Dantzig–Wolfe Decomposition for Solving Belief Multi-Objective Nonlinear Programming Problems with Block Angular Structure

2017 ◽  
Vol 16 (02) ◽  
pp. 333-387 ◽  
Author(s):  
Behnam Vahdani ◽  
Meghdad Salimi ◽  
Seyed Meysam Mousavi
Keyword(s):  
Decision Making ◽  
Nonlinear Programming ◽  
Large Scale ◽  
Dimensional Space ◽  
Independent Solution ◽  
Angular Structure ◽  
Multi Objective ◽  
Model Based ◽  
Solution Methods ◽  
Single Objective

This paper presents an integrated model based on a compromised solution method to solve fuzzy belief multi-objective large-scale nonlinear programming (FBMOLSNLP) problem with block angular structure. A new method is proposed to transfer each belief decision-making problem into some fuzzy problems. Furthermore, we propose a new compromise method of decision-making as one of the most efficient methods based on the particular measure of closeness to the ideal solution to aggregate multi-objective decision-making (MODM) problems into a single problem. The decomposition algorithm based on Dantzig–Wolfe is utilized to reduce the large-dimensional objective space into a two-dimensional space. Then, Zimmerman method is applied to transfer each bi-objective to a single-objective. Moreover, TOPSIS and VIKOR are utilized as two independent solution methods to aggregate each multi-objective sub-problem. Finally, a new single-objective nonlinear programming problem is solved to find the final solution. To justify the proposed model, two illustrative examples are provided, and the results of three decision methods are compromised.

A two-sided matching decision-making approach based on regret theory under intuitionistic fuzzy environment

2021 ◽  
pp. 1-18
Author(s):  
Xiang Jia ◽  
Xinfan Wang ◽  
Yuanfang Zhu ◽  
Lang Zhou ◽  
Huan Zhou
Keyword(s):  
Decision Making ◽  
Hamming Distance ◽  
Optimal Solution ◽  
Intuitionistic Fuzzy Sets ◽  
Regret Theory ◽  
Multi Objective ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Objective Model ◽  
Single Objective

This study proposes a two-sided matching decision-making (TSMDM) approach by combining the regret theory under the intuitionistic fuzzy environment. At first, according to the Hamming distance of intuitionistic fuzzy sets and regret theory, superior and inferior flows are defined to describe the comparative preference of subjects. Hereafter, the satisfaction degrees are obtained by integrating the superior and inferior flows of the subjects. The comprehensive satisfaction degrees are calculated by aggregating the satisfaction degrees, based on which, a multi-objective TSMDM model is built. Furthermore, the multi-objective TSMDM model is converted to a single-objective model, the optimal solution of the latter is derived. Finally, an illustrative example and several analyses are provided to verify the feasibility and the effectiveness of the proposed approach.

scholarly journals Computational cognitive neuroscience: Model fitting should not replace model simulation

2016 ◽  
Author(s):  
Stefano Palminteri ◽  
Valentin Wyart ◽  
Etienne Koechlin
Keyword(s):  
Decision Making ◽  
Cognitive Neuroscience ◽  
Large Scale ◽  
Model Comparison ◽  
Model Simulation ◽  
Model Fitting ◽  
Model Simulations ◽  
Model Based ◽  
Comparison Results ◽  
Future Work

AbstractCognitive neuroscience, especially in the fields of learning and decision-making, is witnessing the blossoming of computational model-based analyses. Several methodological and review papers have indicated how and why candidate models should be compared by trading off their ability to predict the data as a function of their complexity. However, the importance of simulating candidate models has been so far largely overlooked, which entails several drawbacks and leads to invalid conclusions. Here we argue that the analysis of model simulations is often necessary to support the specific claims about behavioral function that most of model-based studies make. We defend this argument both informally by providing a large-scale (N>300) review of recent studies, and formally by showing how model simulations are necessary to interpret model comparison results. Finally, we propose guidelines for future work, which combine model comparison and simulation.

scholarly journals A Survey of Multi-Objective Sequential Decision-Making

2013 ◽  
Vol 48 ◽  
pp. 67-113 ◽  
Author(s):  
D. M. Roijers ◽  
P. Vamplew ◽  
S. Whiteson ◽  
R. Dazeley
Keyword(s):  
Decision Making ◽  
Pareto Front ◽  
Optimal Solution ◽  
Multiple Objectives ◽  
Sequential Decision Making ◽  
Sequential Decision ◽  
Multi Objective ◽  
Scalarization Function ◽  
Future Work ◽  
Single Objective

Sequential decision-making problems with multiple objectives arise naturally in practice and pose unique challenges for research in decision-theoretic planning and learning, which has largely focused on single-objective settings. This article surveys algorithms designed for sequential decision-making problems with multiple objectives. Though there is a growing body of literature on this subject, little of it makes explicit under what circumstances special methods are needed to solve multi-objective problems. Therefore, we identify three distinct scenarios in which converting such a problem to a single-objective one is impossible, infeasible, or undesirable. Furthermore, we propose a taxonomy that classifies multi-objective methods according to the applicable scenario, the nature of the scalarization function (which projects multi-objective values to scalar ones), and the type of policies considered. We show how these factors determine the nature of an optimal solution, which can be a single policy, a convex hull, or a Pareto front. Using this taxonomy, we survey the literature on multi-objective methods for planning and learning. Finally, we discuss key applications of such methods and outline opportunities for future work.

The Implementation of Large-Scale Decision-Making Support Systems

2010 ◽  
pp. 1071-1083
Author(s):  
Manual Mora ◽  
Ovsei Gelman ◽  
Guisseppi Forgionne ◽  
Francisco Cervantes
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Large Scale ◽  
Support Systems ◽  
Model Based ◽  
Knowledge Based ◽  
Decision Making Support

This article reviews the literature-based issues involved in implementing large-scale decision-making support systems (DMSSs). Unlike previous studies, this review studies holistically three types of DMSSs (model-based decision support systems, executive-oriented decision support systems, and knowledge-based decision support systems) and incorporates recent studies on the simulation of the implementations process. Such an article contributes to the literature by organizing the fragmented knowledge on the DMSS implementation phenomenon and by communicating the factors and stages involved in successful or failed large-scale DMSS implementations to practitioners.

scholarly journals Evaluating decision-making units under uncertainty using fuzzy multi-objective nonlinear programming

2016 ◽  
Vol 55 (1) ◽  
pp. 1-15
Author(s):  
Madjid Langroudi Zerafat Angiz ◽  
Mohd Kamal Mohd Nawawi ◽  
Ruzelan Khalid ◽  
Adli Mustafa ◽  
Ali Emrouznejad ◽  
...  
Keyword(s):  
Decision Making ◽  
Nonlinear Programming ◽  
Multi Objective ◽  
Decision Making Units
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