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Year 2019, Volume: 9 Issue: 3, 434 - 445, 01.09.2019

Abstract

References

  • Abbasi Molai, A., (2014), A new algorithm for resolution of the quadratic programming problem with fuzzy relation inequality constraints, Comput. Ind. Eng. 72, pp. 306-314.
  • Fang, S. C., Li, G., (1999), Solving fuzzy relation equations with a linear objective function, Fuzzy Sets Syst. 103, pp. 107-113.
  • Feng, S., Ma, Y., Li, J., (2012), A kind of nonlinear and non-convex optimization problems under mixed fuzzy relational equations constraints with max-min and max-average composition. In: 2012 eighth international conference on computational intelligence and security, Guangzhou, China, 17-18 November, ISBN: 978-1-4673-4725-9.
  • Guo, F. F., Xia, Z. Q., (2006), An algorithm for solving optimization problems with one linear objective function and finitely many constraints of fuzzy relation inequalities, Fuzzy Decis. Maki. Optim. 5, pp. 33-47.
  • Hassanzadeh, R., Khorram, E., Mahdavi, I., Mahdavi-Amiri, N., (2011), A genetic algorithm for optimization problems with fuzzy relation constraints using max-product composition, Appl. Soft Comput. 11, pp. 551-560.
  • Khorram, E., Hassanzadeh, R., (2008), Solving nonlinear optimization problems subjected to fuzzy relation equation constraints with max-average composition using a modified genetic algorithm, Com- put. Ind. Eng. 55, 1-14.
  • Li, P., Fang, S. C., (2008), On the resolution and optimization of a system of fuzzy relational equations with sup-T composition, Fuzzy Optim. Decis. Mak. 7, pp. 169-214.
  • Li, J., Feng, S., Mi, H., (2012), A kind of nonlinear programming problem based on mixed fuzzy relation equations constraints, Phys. Proc. 33, pp. 1717-1724
  • Lu, J. J., Fang, S. C., (2001), Solving nonlinear optimization problems with fuzzy relation equation constraints, Fuzzy Sets Syst. 119, pp. 1-20.
  • Mashayekhi, Z., Khorram, E., (2009), On optimizing a linear objective function subjected to fuzzy relation inequalities, Fuzz. Optim. Deci. Mak. 8, pp. 103-114.
  • Shivanian, E., Khorram, E., (2009), Monomial geometric programming with fuzzy relation inequality constraints with max-product composition, Comput. Ind. Eng. 56, pp. 1386-1392.
  • Wang, P. Z., Zhang, D. Z., Sachez, E., Lee, E. S. (1991), Latticized linear programming and fuzzy relational inequalities, J. Math. Anal. Appl. 159, pp. 72-87.
  • Wu, Y. K., Guu, S. M., Liu, J. Y. C., (2002), An accelerated approach for solving fuzzy relation equations with a linear objective function, IEEE Trans. Fuzzy Syst. 10(4), pp. 552-558.
  • Wu, Y. K., Guu, S. M., (2004), A note on fuzzy relation programming problems with max-strict-t- norm composition, Fuzzy Optim. Decis. Mak. 3(3), pp. 271-278
  • Wu, Y. K., Guu, S. M., Liu, J. Y. C., (2008), Reducing the search space of a linear fractional programming problem under fuzzy relational equations with max-Archimedean t-norm composition, Fuzzy Sets Syst. 159, pp. 3347-3359.
  • Yang, X. P., Zhou, X. G., Cao, B. Y., (2015), Single-variable term semi-latticized fuzzy relation geometric programming with max-product operator, Inf. Sci. 325, pp. 271-287.
  • Yang, X. P., Zhou, X. G., Cao, B. Y., (2016), Latticized linear programming subject to max-product fuzzy relation inequalities with application in wireless communication, Inf. Sci., 358-359, pp. 44-55.
  • Zhang, H. T., Dong, H. M., Ren, R. H., (2003), Programming problem with fuzzy relation inequality constraints, Journal of Liaoning Norm Univ. 3, pp. 231-233.
  • Zhou, X. G., Yang, X. P., Cao, B. Y., (2016), Posynomial geometric programming problem subject to max-min fuzzy relation equations, Inf. Sci. 328, pp. 15-25.

GEOMETRIC FUNCTION OPTIMIZATION SUBJECT TO MIXED FUZZY RELATION INEQUALITY CONSTRAINTS

Year 2019, Volume: 9 Issue: 3, 434 - 445, 01.09.2019

Abstract

In this paper, the mixed fuzzy relation geometric programming problem is considered. The Mixed Fuzzy Relation Inequality MFRI system is an importance extension of FRI. It is shown that its feasible domain is non-convex and completely de- termined by its maximum solution and all its minimal solutions. A combination of the components of maximum solution and one of the minimal solutions solves the optimization problem. Some simpli cation procedures are proposed to solve the problem. An algorithm is nally designed to solve the problem.

References

  • Abbasi Molai, A., (2014), A new algorithm for resolution of the quadratic programming problem with fuzzy relation inequality constraints, Comput. Ind. Eng. 72, pp. 306-314.
  • Fang, S. C., Li, G., (1999), Solving fuzzy relation equations with a linear objective function, Fuzzy Sets Syst. 103, pp. 107-113.
  • Feng, S., Ma, Y., Li, J., (2012), A kind of nonlinear and non-convex optimization problems under mixed fuzzy relational equations constraints with max-min and max-average composition. In: 2012 eighth international conference on computational intelligence and security, Guangzhou, China, 17-18 November, ISBN: 978-1-4673-4725-9.
  • Guo, F. F., Xia, Z. Q., (2006), An algorithm for solving optimization problems with one linear objective function and finitely many constraints of fuzzy relation inequalities, Fuzzy Decis. Maki. Optim. 5, pp. 33-47.
  • Hassanzadeh, R., Khorram, E., Mahdavi, I., Mahdavi-Amiri, N., (2011), A genetic algorithm for optimization problems with fuzzy relation constraints using max-product composition, Appl. Soft Comput. 11, pp. 551-560.
  • Khorram, E., Hassanzadeh, R., (2008), Solving nonlinear optimization problems subjected to fuzzy relation equation constraints with max-average composition using a modified genetic algorithm, Com- put. Ind. Eng. 55, 1-14.
  • Li, P., Fang, S. C., (2008), On the resolution and optimization of a system of fuzzy relational equations with sup-T composition, Fuzzy Optim. Decis. Mak. 7, pp. 169-214.
  • Li, J., Feng, S., Mi, H., (2012), A kind of nonlinear programming problem based on mixed fuzzy relation equations constraints, Phys. Proc. 33, pp. 1717-1724
  • Lu, J. J., Fang, S. C., (2001), Solving nonlinear optimization problems with fuzzy relation equation constraints, Fuzzy Sets Syst. 119, pp. 1-20.
  • Mashayekhi, Z., Khorram, E., (2009), On optimizing a linear objective function subjected to fuzzy relation inequalities, Fuzz. Optim. Deci. Mak. 8, pp. 103-114.
  • Shivanian, E., Khorram, E., (2009), Monomial geometric programming with fuzzy relation inequality constraints with max-product composition, Comput. Ind. Eng. 56, pp. 1386-1392.
  • Wang, P. Z., Zhang, D. Z., Sachez, E., Lee, E. S. (1991), Latticized linear programming and fuzzy relational inequalities, J. Math. Anal. Appl. 159, pp. 72-87.
  • Wu, Y. K., Guu, S. M., Liu, J. Y. C., (2002), An accelerated approach for solving fuzzy relation equations with a linear objective function, IEEE Trans. Fuzzy Syst. 10(4), pp. 552-558.
  • Wu, Y. K., Guu, S. M., (2004), A note on fuzzy relation programming problems with max-strict-t- norm composition, Fuzzy Optim. Decis. Mak. 3(3), pp. 271-278
  • Wu, Y. K., Guu, S. M., Liu, J. Y. C., (2008), Reducing the search space of a linear fractional programming problem under fuzzy relational equations with max-Archimedean t-norm composition, Fuzzy Sets Syst. 159, pp. 3347-3359.
  • Yang, X. P., Zhou, X. G., Cao, B. Y., (2015), Single-variable term semi-latticized fuzzy relation geometric programming with max-product operator, Inf. Sci. 325, pp. 271-287.
  • Yang, X. P., Zhou, X. G., Cao, B. Y., (2016), Latticized linear programming subject to max-product fuzzy relation inequalities with application in wireless communication, Inf. Sci., 358-359, pp. 44-55.
  • Zhang, H. T., Dong, H. M., Ren, R. H., (2003), Programming problem with fuzzy relation inequality constraints, Journal of Liaoning Norm Univ. 3, pp. 231-233.
  • Zhou, X. G., Yang, X. P., Cao, B. Y., (2016), Posynomial geometric programming problem subject to max-min fuzzy relation equations, Inf. Sci. 328, pp. 15-25.
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Details

Primary Language English
Journal Section Research Article
Authors

B. Hedayatfar This is me

A. A. Molai This is me

Publication Date September 1, 2019
Published in Issue Year 2019 Volume: 9 Issue: 3

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