ENHANCED INTERACTIVE SATISFYING OPTIMIZATION APPROACH TO MULTIPLE OBJECTIVE OPTIMIZATION WITH PREEMPTIVE PRIORITIES

2006 ◽  
Vol 05 (01) ◽  
pp. 47-63 ◽  
Author(s):  
CHAOFANG HU ◽  
SHAOYUAN LI
Keyword(s):  
Optimization Problem ◽  
Optimization Method ◽  
Previous Method ◽  
Optimization Models ◽  
Multiple Objective ◽  
Multiple Objective Optimization ◽  
Optimization Approach ◽  
Fuzzy Relations ◽  
Objective Functions ◽  
Preemptive Priority

This paper proposes an enhanced interactive satisfying optimization method based on goal programming for the multiple objective optimization problem with preemptive priorities. Based on the previous method, the approach presented makes the higher priority achieve the higher satisfying degree. For three fuzzy relations of the objective functions, the corresponding optimization models are proposed. Not only can satisfying results for all the objectives be acquired, but the preemptive priority requirement can also be simultaneously actualized. The balance between optimization and priorities is realized. We demonstrate the power of this proposed method by illustrative examples.

TWO-PHASE INTERACTIVE SATISFYING METHOD OF FUZZY MULTIPLE OBJECTIVE OPTIMIZATION WITH LINGUISTIC PREFERENCE

2009 ◽  
Vol 08 (03) ◽  
pp. 427-443 ◽  
Author(s):  
CHAOFANG HU ◽  
SHAOYUAN LI
Keyword(s):  
Decision Maker ◽  
Optimization Problem ◽  
Optimization Method ◽  
Multiple Objectives ◽  
Multiple Objective ◽  
Multiple Objective Optimization ◽  
Two Phase ◽  
Numerical Example ◽  
Complex Optimization ◽  
Important Objective

This paper presents a two-phase interactive satisfying optimization method for fuzzy multiple objectives optimization with linguistic preference. This proposed approach utilizes the view that the more important objective has the higher desirable satisfying degree. The originally complex optimization problem is simplified and divided into two parts that are solved one by one. The decision maker can acquire satisfying solution of all the objectives under linguistic preference. Numerical example shows the efficiency, flexibility, and sensitivity of the proposed method.

scholarly journals Multi-Objective Optimization of Gas Pipeline Networks

Energies ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 5141
Author(s):  
Andrzej J. Osiadacz ◽  
Niccolo Isoli
Keyword(s):  
Optimization Problem ◽  
Optimization Method ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Constrained Optimization Problem ◽  
Nonlinear Constrained Optimization ◽  
Scalar Optimization ◽  
Gas Networks ◽  
Pipeline Networks ◽  
Gas Supply

The main goal of this paper is to prove that bi-objective optimization of high-pressure gas networks ensures grater system efficiency than scalar optimization. The proposed algorithm searches for a trade-off between minimization of the running costs of compressors and maximization of gas networks capacity (security of gas supply to customers). The bi-criteria algorithm was developed using a gradient projection method to solve the nonlinear constrained optimization problem, and a hierarchical vector optimization method. To prove the correctness of the algorithm, three existing networks have been solved. A comparison between the scalar optimization and bi-criteria optimization results confirmed the advantages of the bi-criteria optimization approach.

scholarly journals Enhanced Two-Step Method via Relaxed Order ofα-Satisfactory Degrees for Fuzzy Multiobjective Optimization

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Na Wang ◽  
Chaofang Hu ◽  
Wuxi Shi ◽  
Chunbo Xiu ◽  
Yimei Chen
Keyword(s):  
Multiobjective Optimization ◽  
Set Theory ◽  
Optimization Problem ◽  
Fuzzy Numbers ◽  
Fuzzy Relations ◽  
Preemptive Priority ◽  
Step Method ◽  
Satisfactory Solution ◽  
Order Constraint ◽  
Fuzzy Parameters

An enhanced two-step method via relaxed order of satisfactory degrees for fuzzy multiobjective optimization is proposed in this paper. By introducing the concept of fuzzy numbers andα-level set theory, fuzzy parameters are taken as variables, and all the objectives are transformed into fuzzy goals involving three fuzzy relations. The order ofα-satisfactory degrees which means the objectives with higher priority achieving higher satisfactory degree is applied to model preemptive priority requirement. This strict order constraint is relaxed by priority variable to find the preferred solution satisfying optimization and priority. The original optimization problem is divided into two steps to be solved iteratively. The M-α-Pareto optimality of the solution is ensured, and the satisfactory solution can be acquired by regulating the slack parameterΔδor changingα. The numerical examples demonstrate the power of the proposed method.

J1030205 Identification of Dynamic Structural Model Using Multiple Objective Optimization Method

2015 ◽  
Vol 2015 (0) ◽  
pp. _J1030205--_J1030205- ◽  
Author(s):  
Yuki MIMURA ◽  
Masayuki ICHIMONJI ◽  
Kyohei HIRAI ◽  
Toshikazu NAGATA ◽  
Toshiaki HIRATE ◽  
...  
Keyword(s):  
Structural Model ◽  
Optimization Method ◽  
Multiple Objective ◽  
Multiple Objective Optimization ◽  
Dynamic Structural Model

Robust Optimization of an Accelerometer Considering Fabrication Errors

2009 ◽  
Vol 628-629 ◽  
pp. 353-356 ◽  
Author(s):  
Guang Jun Liu ◽  
Tao Jiang ◽  
An Lin Wang
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Sensitivity Analysis ◽  
Robust Optimization ◽  
Optimization Problem ◽  
Design Space ◽  
Optimization Approach ◽  
Objective Functions ◽  
Micro Fabrication ◽  
Fabrication Errors

A robust optimization approach of an accelerometer is presented to minimize the effect of variations from micro fabrication. The sensitivity analysis technology is employed to reduce design space and to find the key parameters that have greatest influence on the accelerometer. And then, the constraint conditions and objective functions for robust optimization and the corresponding mathematical model are presented. The optimization problem is solved by the Multiple-island Genetic Algorithm and the results show that an accelerometer with better performance is obtained.

scholarly journals Comparison of Planar Parallel Manipulator Architectures Based on a Multi-Objective Design Optimization Approach

2010 ◽  
Author(s):  
Damien Chablat ◽  
Ste´phane Caro ◽  
Raza Ur-Rehman ◽  
Philippe Wenger
Keyword(s):  
Genetic Algorithm ◽  
Design Optimization ◽  
Parallel Manipulator ◽  
Optimization Problem ◽  
Optimization Approach ◽  
Objective Functions ◽  
Multi Objective ◽  
Planar Parallel Manipulator ◽  
Moving Platform ◽  
Pareto Frontiers

This paper deals with the comparison of planar parallel manipulator architectures based on a multi-objective design optimization approach. The manipulator architectures are compared with regard to their mass in motion and their regular workspace size, i.e., the objective functions. The optimization problem is subject to constraints on the manipulator dexterity and stiffness. For a given external wrench, the displacements of the moving platform have to be smaller than given values throughout the obtained maximum regular dexterous workspace. The contributions of the paper are highlighted with the study of 3-PRR, 3-RPR and 3-RRR planar parallel manipulator architectures, which are compared by means of their Pareto frontiers obtained with a genetic algorithm.

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