Adaptive Sampling Detection Based Immune Optimization Approach and Its Application to Chance Constrained Programming

2015 ◽  
pp. 19-28 ◽  
Author(s):  
Kai Yang ◽  
Zhuhong Zhang
Keyword(s):  
Adaptive Sampling ◽  
Chance Constrained Programming ◽  
Optimization Approach ◽  
Immune Optimization ◽  
Constrained Programming

Noisy Immune Optimization for Chance-Constrained Programming Problems

2011 ◽  
Vol 48-49 ◽  
pp. 740-744 ◽  
Author(s):  
Zhu Hong Zhang
Keyword(s):  
Adaptive Sampling ◽  
Chance Constrained Programming ◽  
Noisy Environments ◽  
Immune Optimization ◽  
Noise Compensation ◽  
Noisy Information ◽  
Objective Chance ◽  
And Performance ◽  
Constrained Programming ◽  
Optimization Mechanism

This work puts forward a parameter-less and practical immune optimization mechanism in noisy environments to deal with single-objective chance-constrained programming problems without prior noisy information. In this practical mechanism, an adaptive sampling scheme and a new concept of reliability-dominance are established to evaluate individuals, while three immune operators borrowed from several simplified immune metaphors in the immune system and the idea of fitness inheritance are utilized to evolve the current population, in order to weaken noisy influence to the optimized quality. Under the mechanism, three kinds of algorithms are obtained through changing its mutation rule. Experimental results show that the mechanism can achieve satisfactory performances including the quality of optimization, noise compensation and performance efficiency.

Optimization Methods in Modeling the Mechanical Properties of Heavy Steel Plates / Metody Optymalizacyjne W Modelowaniu Własności Mechanicznych Blach Grubych

2012 ◽  
Vol 57 (4) ◽  
pp. 971-979
Author(s):  
A.Z. Grzybowski
Keyword(s):  
Mechanical Properties ◽  
Steel Production ◽  
Optimization Methods ◽  
Linear Constraints ◽  
Steel Plates ◽  
Chance Constrained Programming ◽  
Optimization Approach ◽  
Industrial Manufacturing ◽  
Optimization Task ◽  
Constrained Programming

The paper is devoted to an optimization approach to a problem of statistical modeling of mechanical properties of heavy steel plates during a real industrial manufacturing process. The approach enables the manufacturer to attain a specific set of the final product properties by optimizing the alloying composition within the grade specifications. Because this composition has to stay in the agreement with earlier indicated specifications, it leads to the large system of linear constraints, and the problem itself can be expressed in the form of linear programming (LP) task. It turns out however, that certain of the constraints contain the coefficients which have to be estimated on the base of the data gathered in the production process and as such they are uncertain. Consequently, the initial optimization task should be modeled as so-called Chance Constrained Programming problem (CCP), which is a special class within the stochastic programming problems. The paper presents mathematical models of the optimization problem that result from both approaches and indicates differences which are important for the decision makers in the production practice. Some examples illustrating the differences in solutions resulting from LP and CCP models are presented as well. Although the statistical analysis presented in this paper is based on the data gathered in the ISD Czestochowa Steelworks, the proposed approach can be adopted in any other process of steel production.

Chance constrained programming with some non-normal continuous random variables

OPSEARCH ◽  
2020 ◽  
Vol 57 (4) ◽  
pp. 1281-1298
Author(s):  
D. K. Mohanty ◽  
Avik Pradhan ◽  
M. P. Biswal
Keyword(s):  
Random Variables ◽  
Chance Constrained Programming ◽  
Constrained Programming

A novel model for multi-criteria assessment based on BWM and possibilistic chance-constrained programming

2021 ◽  
pp. 107287
Author(s):  
Maghsoud Amiri ◽  
Mohammad Hashemi-Tabatabaei ◽  
Mohammad Ghahremanloo ◽  
Mehdi Keshavarz-Ghorabaee ◽  
Edmundas Kazimieras Zavadskas ◽  
...  
Keyword(s):  
Chance Constrained Programming ◽  
Constrained Programming ◽  
Novel Model
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