An Innovative Genetic Algorithms-Based Inexact Non-Linear Programming Problem Solving Method - Journal of Environmental Protection

JEP > Vol.8 No.3, March 2017

Journal of Environmental Protection

Volume 8, Issue 3 (March 2017)

ISSN Print: 2152-2197 ISSN Online: 2152-2219

Google-based Impact Factor: 1.15 Citations h5-index & Ranking

An Innovative Genetic Algorithms-Based Inexact Non-Linear Programming Problem Solving Method ()

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DOI: 10.4236/jep.2017.83018 1,684 Downloads 3,432 Views Citations

Author(s)

Weihua Jin, Zhiying Hu^*, Christine Chan

Affiliation(s)

Energy Informatics Laboratory, Faculty of Engineering & Applied Science. University of Regina, Regina, SK, Canada.

ABSTRACT

In this paper, an innovative Genetic Algorithms (GA)-based inexact non-linear programming (GAINLP) problem solving approach has been proposed for solving non-linear programming optimization problems with inexact information (inexact non-linear operation programming). GAINLP was developed based on a GA-based inexact quadratic solving method. The Genetic Algorithm Solver of the Global Optimization Toolbox (GASGOT) developed by MATLAB^TM was adopted as the implementation environment of this study. GAINLP was applied to a municipality solid waste management case. The results from different scenarios indicated that the proposed GA-based heuristic optimization approach was able to generate a solution for a complicated nonlinear problem, which also involved uncertainty.

KEYWORDS

Genetic Algorithms, Inexact Non-Linear Programming (INLP), Economy of Scale, Numeric Optimization, Solid Waste Management

Share and Cite:

Jin, W. , Hu, Z. and Chan, C. (2017) An Innovative Genetic Algorithms-Based Inexact Non-Linear Programming Problem Solving Method. Journal of Environmental Protection, 8, 231-249. doi: 10.4236/jep.2017.83018.

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