Mathematics and Statistics Faculty and Staff Publications

Document Type

Book

Publication Date

2018

Abstract

In the real world, uncertainty or vagueness is prevalent in engineering and management computations. Commonly, such uncertainties are included in the design process by introducing simplified hypothesis and safety or design factors. In case of structural and pavement design, several design methods are available to optimize objectives. But all such methods follow numerous monographs, tables and charts to find effective thickness of pavement design or optimum weight and deflection of structure calculating certain loop of algorithm in the cited iteration process. Most of the time, designers either only take help of a software or stop the cited procedure even after two or three iterations. As for example, the finite element method and genetic algorithm type of crisp optimization method had been applied on the cited topic, where the values of the input parameters were obtained from experimental data in laboratory scale. But practically, above cited standards have already ranged the magnitude of those parameters in between maximum to the minimum values. As such, the designer becomes puzzled to select those input parameters from such ranges which actually yield imprecise parameters or goals with three key governing factors i.e. degrees of acceptance, rejection and hesitancy, requiring fuzzy, intuitionistic fuzzy, and neutrosophic optimization. Therefore, the problem of structural designs, pavement designs, welded beam designs are firstly classified into single objective and multi-objective problems of structural systems. Then, a mathematical algorithm - e.g. Neutrosophic Geometric Programming, Neutrosophic Linear Programming Problem, Single Objective Neutrosophic Optimization...

Publisher

Pons, Brussels

ISSN

9781599735436

Language (ISO)

English

Keywords

uncertainty, vagueness, engineering, management

Creative Commons License

Creative Commons Attribution-Share Alike 4.0 License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 License.

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