JOURNAL ARTICLE

Mixed-Type Duality on Nonsmooth Minimax Fractional Programming Involving Exponential (p, r)-Invexity

Shun-Chin HoHang–Chin Lai

Year: 2014 Journal:   Numerical Functional Analysis and Optimization Vol: 35 (12)Pages: 1560-1578   Publisher: Taylor & Francis

Abstract

Considering a nonsmooth minimax fractional programming problem involving exponential (p, r)-invexity, we construct a mixed-type dual problem, which is performed by an incomplete Lagrangian dual model. This mixed-type dual model involves the Wolfe type dual and Mond-Weir type dual as the special cases under exponential (p, r)-invexity. We establish the mixed-type duality problem with conditions for exponential (p, r)-invexity and prove that the optimal values of the primary problem and the mixed-type duality problem have no duality gap under the framwork of exponential (p, r)-invexity.

Keywords:
Mathematics Duality (order theory) Minimax Type (biology) Exponential type Exponential function Duality gap Applied mathematics Dual (grammatical number) Pure mathematics Mathematical analysis Mathematical optimization Optimization problem

Metrics

4
Cited By
1.00
FWCI (Field Weighted Citation Impact)
22
Refs
0.79
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Optimization and Variational Analysis
Physical Sciences →  Computer Science →  Computational Theory and Mathematics
Optimization and Mathematical Programming
Physical Sciences →  Engineering →  Control and Systems Engineering
Advanced Optimization Algorithms Research
Physical Sciences →  Mathematics →  Numerical Analysis

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