An Analytical Study of Optimization Techniques Using Linear and Nonlinear Programming Models Article Swipe
Atharv Y Mardhe
,
Shinde Rushikesh
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.17920962
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.17920962
Optimization plays a vital role in solving real-world engineering, management, and scientific problems. This paper presents an analytical study of linear and nonlinear programming techniques used for optimal decision-making under constraints. The study focuses on mathematical formulation, solution procedures, and comparative performance of classical optimization methods such as the simplex method, graphical method, Karush–Kuhn–Tucker (KKT) conditions, and gradient-based techniques. Several numerical case studies are included to demonstrate the applicability of these methods in production planning, cost minimization, and resource allocation problems. The results show that linear programming is efficient for proportional systems, whereas nonlinear programming provides greater flexibility for complex engineering systems. The study concludes that optimization techniques significantly enhance system performance and decision accuracy in multidisciplinary applications.
Related Topics
Concepts
Simplex algorithm
Mathematical optimization
Linear programming
Computer science
Nonlinear programming
Flexibility (engineering)
Nonlinear system
Robust optimization
Linear-fractional programming
Multidisciplinary design optimization
Engineering optimization
Optimization problem
Goal programming
Mathematical model
Constrained optimization
Simplex
Stochastic programming
Fractional programming
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.5281/zenodo.17920962
- OA Status
- green
- OpenAlex ID
- https://openalex.org/W7115075592
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W7115075592Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5281/zenodo.17920962Digital Object Identifier
- Title
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An Analytical Study of Optimization Techniques Using Linear and Nonlinear Programming ModelsWork title
- Type
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articleOpenAlex work type
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-12-13Full publication date if available
- Authors
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Atharv Y Mardhe, Shinde RushikeshList of authors in order
- Landing page
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https://doi.org/10.5281/zenodo.17920962Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://doi.org/10.5281/zenodo.17920962Direct OA link when available
- Concepts
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Simplex algorithm, Mathematical optimization, Linear programming, Computer science, Nonlinear programming, Flexibility (engineering), Nonlinear system, Robust optimization, Linear-fractional programming, Multidisciplinary design optimization, Engineering optimization, Optimization problem, Goal programming, Mathematical model, Constrained optimization, Simplex, Stochastic programming, Fractional programmingTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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