Generalized parameter-free duality models in discrete minmax fractional programming based on second-order optimality conditions

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This article discusses the construction of six generalized second-order parameter-free duality models, and proves several weak, strong, and strict converse duality theorems for a discrete minmax fractional programming problem using two partitioning schemes and various types of generalized second-order (ℱ, β, ɸ, 𝜌, θ, 𝑚)-univexity assumptions.

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15 p.

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Zalmai, G. J. & Verma, Ram U. November 8, 2016.

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This article discusses the construction of six generalized second-order parameter-free duality models, and proves several weak, strong, and strict converse duality theorems for a discrete minmax fractional programming problem using two partitioning schemes and various types of generalized second-order (ℱ, β, ɸ, 𝜌, θ, 𝑚)-univexity assumptions.

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15 p.

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  • Mathematical Sciences, 2016. London, UK: Springer

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  • Publication Title: Mathematical Sciences
  • Volume: 10
  • Issue: 4
  • Pages: 185-199
  • Peer Reviewed: Yes

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UNT Scholarly Works

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  • November 8, 2016

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  • March 31, 2017, 9:51 a.m.

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Zalmai, G. J. & Verma, Ram U. Generalized parameter-free duality models in discrete minmax fractional programming based on second-order optimality conditions, article, November 8, 2016; London, UK. (digital.library.unt.edu/ark:/67531/metadc967166/: accessed October 19, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Arts and Sciences.