caa a22 4500 605469725 CHVBK 20210128100324.0 cr unu---uuuuu 210128e20151001xx s 000 0 eng 10.1007/s00500-014-1464-9 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1464-9 Abbasi Molai Ali School of Mathematics and Computer Sciences, Damghan University, P.O.Box 36715-364, Damghan, Iran aut Linear optimization with mixed fuzzy relation inequality constraints using the pseudo-t-norms and its application [Elektronische Daten] [Ali Abbasi Molai] This paper studies the minimization problem of a linear objective function subject to mixed fuzzy relation inequalities (MFRIs) over finite support with regard to max- $$T_1$$ T 1 and max- $$T_2$$ T 2 composition operators, where $$T_1$$ T 1 and $$T_2$$ T 2 are two pseudo-t-norms. We first determine the structure of its feasible domain and then show that the solution set of a MFRI system is determined by a maximum solution and a finite number of minimal solutions. Moreover, sufficient and necessary conditions are proposed to check whether the feasible domain of the problem is empty or not. The MFRI path is defined to determine the minimal solutions of its feasible domain. The resolution process of the optimization problem is also designed based on the structure of its feasible domain. Procedures are proposed to reduce the size of the problem. With regard to the above points and the procedures, an algorithm is designed to solve the problem. Its application is expressed in the area of investing and covering. Finally, the algorithm is compared with other approaches. Springer-Verlag Berlin Heidelberg, 2014 Max-pseudo-t-norm composition nationallicence Mixed fuzzy relation inequality nationallicence Non-convex optimization nationallicence Minimal solution nationallicence Maximum solution nationallicence Soft Computing Springer Berlin Heidelberg 19/10(2015-10-01), 3009-3027 1432-7643 19:10<3009 2015 19 500 https://doi.org/10.1007/s00500-014-1464-9 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1464-9 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Abbasi Molai Ali School of Mathematics and Computer Sciences, Damghan University, P.O.Box 36715-364, Damghan, Iran aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/10(2015-10-01), 3009-3027 1432-7643 19:10<3009 2015 19 500