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Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Innovative Hybrid Genetic Algorithms and Line Search Method for Industrial Production Management

Innovative Hybrid Genetic Algorithms and Line Search Method for Industrial Production Management
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Author(s): Pandian Vasant (Universiti Teknologi PETRONAS, Malaysia)
Copyright: 2012
Pages: 18
Source title: Computer Engineering: Concepts, Methodologies, Tools and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-61350-456-7.ch615

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Abstract

Many engineering, science, information technology and management optimization problems can be considered as non linear programming real world problems where the all or some of the parameters and variables involved are uncertain in nature. These can only be quantified using intelligent computational techniques such as evolutionary computation and fuzzy logic. The main objective of this research chapter is to solve non linear fuzzy optimization problem where the technological coefficient in the constraints involved are fuzzy numbers which was represented by logistic membership functions by using hybrid evolutionary optimization approach. To explore the applicability of the present study a numerical example is considered to determine the production planning for the decision variables and profit of the company.

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