Multiobjective Problem Reduction Search

1999 ◽  
pp. 75-96
Author(s):  
Pallab Dasgupta ◽  
P. P. Chakrabarti ◽  
S. C. DeSarkar
Keyword(s):  
Multiobjective Problem ◽  
Problem Reduction

A Problem-Reduction Approach to Proving Simulation Between Programs

1976 ◽  
Vol SE-2 (2) ◽  
pp. 87-96 ◽  
Author(s):  
A. Birman ◽  
W.H. Joyner
Keyword(s):  
Problem Reduction ◽  
Reduction Approach

Formal Solution of N-Type Taguchi Parameter Design Problems With Stochastic Noise Factors

1991 ◽  
Author(s):  
Nestor F. Michelena ◽  
Alice M. Agogino
Keyword(s):  
Performance Characteristic ◽  
Degrees Of Freedom ◽  
Formal Solution ◽  
Parameter Design ◽  
Absolute Deviation ◽  
Design Problems ◽  
Problem Reduction ◽  
Stochastic Parameters ◽  
Noise Factors ◽  
Monotonicity Analysis

Abstract The Taguchi method of product design is a statistical experimental technique aimed at reducing the variance of a product performance characteristic due to uncontrollable factors. The goal of this paper is to provide a monotonicity analysis based methodology to facilitate the solution of N-type parameter design problems. The obtained design is robust, i.e., the least sensitive to variations on uncontrollable factors (noise). The performance characteristic is unbiased in the sense that its expected value equals a target or specification. The proposed loss function is based on the absolute deviation of the characteristic with respect to the target, instead of the common square error approach. Conditions, like those imposed by monotonicity analysis, on the monotonic characteristics of the performance function are proven, despite the objective function is not monotonic and contains stochastic parameters. These conditions allow the qualitative analysis of the problem to identify the activity of some constraints. Identification of active sets of constraints allows a problem reduction strategy to be employed, where the solution to the original problem is obtained by solving a set of problems with fewer degrees of freedom. Results for the case of one uncontrollable factor are independent of the probability measure on the factor. However, conclusions for the multi-parametric case must take into account the characteristics of the probability space on which the random parameters are defined.

scholarly journals Problem reduction, renormalization, and memory

2006 ◽  
Vol 1 (1) ◽  
pp. 1-27 ◽  
Author(s):  
Alexandre Chorin ◽  
Panagiotis Stinis
Keyword(s):  
Problem Reduction

scholarly journals Multiobjective PID controller design for active suspension system: scalarization approach

2018 ◽  
Vol 8 (2) ◽  
pp. 183-194
Author(s):  
O. Tolga Altinoz
Keyword(s):  
Controller Design ◽  
Optimization Algorithms ◽  
Active Suspension ◽  
Suspension System ◽  
Peak Time ◽  
Tuning Method ◽  
Pid Tuning ◽  
Multiobjective Problem ◽  
The Time Domain ◽  
Single Objective

In this study, the PID tuning method (controller design scheme) is proposed for a linear quarter model of active suspension system installed on the vehicles. The PID tuning scheme is considered as a multiobjective problem which is solved by converting this multiobjective problem into single objective problem with the aid of scalarization approaches. In the study, three different scalarization approaches are used and compared to each other. These approaches are called linear scalarization (weighted sum), epsilon-constraint and Benson’s methods. The objectives of multiobjective optimization are selected from the time-domain properties of the transient response of the system which are overshoot, rise time, peak time and error (in total there are four objectives). The aim of each objective is to minimize the corresponding property of the time response of the system. First, these four objective is applied to the scalarization functions and then single objective problem is obtained. Finally, these single objective problems are solved with the aid of heuristic optimization algorithms. For this purpose, four optimization algorithms are selected, which are called Particle Swarm Optimization, Differential Evolution, Firefly, and Cultural Algorithms. In total,twelve implementations are evaluated with the same number of iterations. In this study, the aim is to compare the scalarization approaches and optimization algorithm on active suspension control problem. The performance of the corresponding cases (implementations) are numerically and graphically demonstrated on transient responses of the system.

Modifying Transactional Databases to Hide Sensitive Association Rules

2021 ◽  
Author(s):  
Syam Menon ◽  
Abhijeet Ghoshal ◽  
Sumit Sarkar
Keyword(s):  
Supply Chain ◽  
Association Rules ◽  
Association Rule ◽  
Sensitive Information ◽  
Data Set ◽  
Problem Reduction ◽  
Transactional Databases ◽  
Potential Risks ◽  
Integer Formulations ◽  
Number Of Firms

Although firms recognize the value in sharing data with supply chain partners, many remain reluctant to share for fear of sensitive information potentially making its way to competitors. Approaches that can help hide sensitive information could alleviate such concerns and increase the number of firms that are willing to share. Sensitive information in transactional databases often manifests itself in the form of association rules. The sensitive association rules can be concealed by altering transactions so that they remain hidden when the data are mined by the partner. The problem of hiding these rules in the data are computationally difficult (NP-hard), and extant approaches are all heuristic in nature. To our knowledge, this is the first paper that introduces the problem as a nonlinear integer formulation to hide the sensitive association rule while minimizing the alterations needed in the data set. We apply transformations that linearize the constraints and derive various results that help reduce the size of the problem to be solved. Our results show that although the nonlinear integer formulations are not practical, the linearizations and problem-reduction steps make a significant impact on solvability and solution time. This approach mitigates potential risks associated with sharing and should increase data sharing among supply chain partners.

RESOLUTION AND PROBLEM REDUCTION FORMAT

1978 ◽  
pp. 335-391
Author(s):  
DONALD W. LOVELAND
Keyword(s):  
Problem Reduction
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