American Institute of Mathematical Sciences

Advanced
January  2013, 9(1): 131-142. doi: 10.3934/jimo.2013.9.131

Optimality conditions and duality in nondifferentiable interval-valued programming

Yuhua Sun 1, and  Laisheng Wang 2,

1. 

School of Mathematics and Physics, University of Science and Technology, Beijing, 100083, China
2. 

College of Science, China Agricultural University, 100083, China

Received  March 2012 Revised  May 2012 Published  December 2012

In this paper, we define the concepts of $LU$ optimal solution to interval-valued programming problem. By considering the concepts of $LU$ optimal solution, the Fritz John type and Kuhn-Tucker type necessary and sufficient optimality conditions for nondifferentiable interval programming are derived. Further, we establish the dual problem and prove the duality theorems.
Keywords: duality, interval mathematics., necessary optimality conditions, sufficient optimality conditions, Interval-valued programming.
Mathematics Subject Classification: 90C46, 90C3.
Citation: Yuhua Sun, Laisheng Wang. Optimality conditions and duality in nondifferentiable interval-valued programming. Journal of Industrial & Management Optimization, 2013, 9 (1) : 131-142. doi: 10.3934/jimo.2013.9.131
References:
[1]

T. Fu. Liang and H. Wen. Cheng, Multi-objective aggregate production planning decisions using two-phase fuzzy goal programming method, Journal of Industrial and Management Optimization, 7 (2011), 365-383.  Google Scholar

[2]

J. Ramík, Duality in fuzzy linear programming: some new concepts and results, Fuzzy Optimization and Decision Making, 4 (2005), 25-39.  Google Scholar

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N. M. Amiri and S. H. Nasseri, Duality in fuzzy number linear programming by use of a certain linear ranking function, Applied Mathematics and Computation, 180 (2006), 206-216. doi: 10.1016/j.amc.2005.11.161.  Google Scholar

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J. Ramík, Optimal solutions in optimization problem with objective function depending on fuzzy parameters, Fuzzy Sets and Systems, 158 (2007), 1873-1881. doi: 10.1016/j.fss.2007.04.003.  Google Scholar

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C. Zhang, X. Yuan and E. S. Lee, Duality theory in fuzzy mathematical programming problems with fuzzy coefficients, Computers and Mathematics with Applications, 49 (2005), 1709-1730.  Google Scholar

[6]

H. C. Wu, Duality theory in fuzzy optimization problems formulated by the Wolfe's primal and dual pair, Fuzzy Optimization and Decision Making, 6 (2007), 179-198. doi: 10.1007/s10700-007-9014-x.  Google Scholar

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H. C. Wu, Duality theorems in fuzzy mathematical programming problems based on the concept of necessity, Fuzzy Sets and Systems, 139 (2003), 363-377. doi: 10.1016/S0165-0114(02)00575-4.  Google Scholar

[8]

H. C. Wu, Duality theory in fuzzy optimization problems, Fuzzy Optimization and Decision Making, 3 (2004), 345-365.  Google Scholar

[9]

Z. T. Gong and H. X. Li, Saddle point optimality conditions in fuzzy optimization problems, Fuzzy Information and Engineering, AISC, 2 (2009), 7-14. Google Scholar

[10]

H. C. Wu, The optimality conditions for optimization problems with convex constraints and multiple fuzzy-valued objective functions, Fuzzy Optimization and Decision Making, 8 (2009), 295-321.  Google Scholar

[11]

D. Dentcheva and W. Römisch , Duality gaps in nonconvex stochastic optimization, Mathematical Programming, Ser. A, 101 (2004), 515-535.  Google Scholar

[12]

L. A. Korf, Stochastic programming duality: $L^{\propto}$ multipliers for unbounded constraints with an application to mathematical finance, Mathematical Programming, Ser. A, 99 (2004), 241-259.  Google Scholar

[13]

D. Dentcheva and A.Ruszczyński, Optimality and duality theory for stochastic optimization problems with nonlinear dominance constraints, Mathematical Programming, Ser. A, 99 (2004), 329-350.  Google Scholar

[14]

A. Shapiro, Stochastic programming approach to optimization under uncertainty, Mathematical Programming, Ser. B, 112 (2008), 183-220.  Google Scholar

[15]

H. Zhu, Convex duality for finite-fuel problems in singular stochastic control, Journal of Optimization Theory and Applications, 75 (1992), 154-181.  Google Scholar

[16]

H. C. Wu, Duality theory for optimization problems with interval-valued objective functions, Journal of Optimization Theory and Applications, 144 (2010), 615-628.  Google Scholar

[17]

H. C. Wu, On interval-valued nonlinear programming problems, Journal of Mathematical Analysis and Application, 338 (2008), 299-316.  Google Scholar

[18]

H. C. Wu, Wolfe duality for interval-valued optimization, Journal of Optimization Theory and Applications, 138 (2008), 497-509.  Google Scholar

[19]

H. C. Zhou and Y. J. Wang, Optimality condition and mixed duality for interval-valued optimization. Fuzzy Information and Engineering, AISC, 62 (2009), 1315-1323. Google Scholar

[20]

H. C. Wu, The Karush-Kuhn-Tucker optimality conditions in an optimization problem with interval-valued objective function, European Journal of Operational Research, 176 (2007), 46-59.  Google Scholar

[21]

H. C. Wu, The Karush-Kuhn-Tucker optimality conditions in multiobjective programming problems with interval-valued objective functions, European Journal of Operational Research, 196 (2009), 49-60.  Google Scholar

[22]

R. E. Moore, "Method and Applications of Interval Analysis," SIAM, Philadelphia, 1979.  Google Scholar

[23]

A. Prékopa, "Stochastic Programming: Mathematics and Its Applications," Kluwer Academic Publishers Group, Dordrecht, 1995.  Google Scholar

[24]

M. Schechter, More on subgradient duality, Journal of Mathematical Analysis and Application, 71 (1979), 251-262.  Google Scholar

show all references

References:
[1]

T. Fu. Liang and H. Wen. Cheng, Multi-objective aggregate production planning decisions using two-phase fuzzy goal programming method, Journal of Industrial and Management Optimization, 7 (2011), 365-383.  Google Scholar

[2]

J. Ramík, Duality in fuzzy linear programming: some new concepts and results, Fuzzy Optimization and Decision Making, 4 (2005), 25-39.  Google Scholar

[3]

N. M. Amiri and S. H. Nasseri, Duality in fuzzy number linear programming by use of a certain linear ranking function, Applied Mathematics and Computation, 180 (2006), 206-216. doi: 10.1016/j.amc.2005.11.161.  Google Scholar

[4]

J. Ramík, Optimal solutions in optimization problem with objective function depending on fuzzy parameters, Fuzzy Sets and Systems, 158 (2007), 1873-1881. doi: 10.1016/j.fss.2007.04.003.  Google Scholar

[5]

C. Zhang, X. Yuan and E. S. Lee, Duality theory in fuzzy mathematical programming problems with fuzzy coefficients, Computers and Mathematics with Applications, 49 (2005), 1709-1730.  Google Scholar

[6]

H. C. Wu, Duality theory in fuzzy optimization problems formulated by the Wolfe's primal and dual pair, Fuzzy Optimization and Decision Making, 6 (2007), 179-198. doi: 10.1007/s10700-007-9014-x.  Google Scholar

[7]

H. C. Wu, Duality theorems in fuzzy mathematical programming problems based on the concept of necessity, Fuzzy Sets and Systems, 139 (2003), 363-377. doi: 10.1016/S0165-0114(02)00575-4.  Google Scholar

[8]

H. C. Wu, Duality theory in fuzzy optimization problems, Fuzzy Optimization and Decision Making, 3 (2004), 345-365.  Google Scholar

[9]

Z. T. Gong and H. X. Li, Saddle point optimality conditions in fuzzy optimization problems, Fuzzy Information and Engineering, AISC, 2 (2009), 7-14. Google Scholar

[10]

H. C. Wu, The optimality conditions for optimization problems with convex constraints and multiple fuzzy-valued objective functions, Fuzzy Optimization and Decision Making, 8 (2009), 295-321.  Google Scholar

[11]

D. Dentcheva and W. Römisch , Duality gaps in nonconvex stochastic optimization, Mathematical Programming, Ser. A, 101 (2004), 515-535.  Google Scholar

[12]

L. A. Korf, Stochastic programming duality: $L^{\propto}$ multipliers for unbounded constraints with an application to mathematical finance, Mathematical Programming, Ser. A, 99 (2004), 241-259.  Google Scholar

[13]

D. Dentcheva and A.Ruszczyński, Optimality and duality theory for stochastic optimization problems with nonlinear dominance constraints, Mathematical Programming, Ser. A, 99 (2004), 329-350.  Google Scholar

[14]

A. Shapiro, Stochastic programming approach to optimization under uncertainty, Mathematical Programming, Ser. B, 112 (2008), 183-220.  Google Scholar

[15]

H. Zhu, Convex duality for finite-fuel problems in singular stochastic control, Journal of Optimization Theory and Applications, 75 (1992), 154-181.  Google Scholar

[16]

H. C. Wu, Duality theory for optimization problems with interval-valued objective functions, Journal of Optimization Theory and Applications, 144 (2010), 615-628.  Google Scholar

[17]

H. C. Wu, On interval-valued nonlinear programming problems, Journal of Mathematical Analysis and Application, 338 (2008), 299-316.  Google Scholar

[18]

H. C. Wu, Wolfe duality for interval-valued optimization, Journal of Optimization Theory and Applications, 138 (2008), 497-509.  Google Scholar

[19]

H. C. Zhou and Y. J. Wang, Optimality condition and mixed duality for interval-valued optimization. Fuzzy Information and Engineering, AISC, 62 (2009), 1315-1323. Google Scholar

[20]

H. C. Wu, The Karush-Kuhn-Tucker optimality conditions in an optimization problem with interval-valued objective function, European Journal of Operational Research, 176 (2007), 46-59.  Google Scholar

[21]

H. C. Wu, The Karush-Kuhn-Tucker optimality conditions in multiobjective programming problems with interval-valued objective functions, European Journal of Operational Research, 196 (2009), 49-60.  Google Scholar

[22]

R. E. Moore, "Method and Applications of Interval Analysis," SIAM, Philadelphia, 1979.  Google Scholar

[23]

A. Prékopa, "Stochastic Programming: Mathematics and Its Applications," Kluwer Academic Publishers Group, Dordrecht, 1995.  Google Scholar

[24]

M. Schechter, More on subgradient duality, Journal of Mathematical Analysis and Application, 71 (1979), 251-262.  Google Scholar

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