In this paper, we investigate multiobjective generalized semi-infinite optimization problems with nondifferentiable convex data. We introduce several upper-level qualification conditions of Cottle-type for both the constraints and the data. Based on these qualification conditions, we establish first-order necessary optimality conditions of Fritz–John, Karush–Kuhn–Tucker, and strong Karush–Kuhn–Tucker types for weakly efficient solutions of the considered problems. The results are derived using tools from convex analysis.
Kanzi,N and Niknam,S . (2025). Necessary Optimality Conditions for Weakly Efficient Solutions in Convex Multiobjective GSIPs. Journal of Applied Mathematics & Data Analytics, 1(2), 1-14. doi: 10.311581/JAMDA.2509.1007.1.2.1
MLA
Kanzi,N , and Niknam,S . "Necessary Optimality Conditions for Weakly Efficient Solutions in Convex Multiobjective GSIPs", Journal of Applied Mathematics & Data Analytics, 1, 2, 2025, 1-14. doi: 10.311581/JAMDA.2509.1007.1.2.1
HARVARD
Kanzi N, Niknam S. (2025). 'Necessary Optimality Conditions for Weakly Efficient Solutions in Convex Multiobjective GSIPs', Journal of Applied Mathematics & Data Analytics, 1(2), pp. 1-14. doi: 10.311581/JAMDA.2509.1007.1.2.1
CHICAGO
N Kanzi and S Niknam, "Necessary Optimality Conditions for Weakly Efficient Solutions in Convex Multiobjective GSIPs," Journal of Applied Mathematics & Data Analytics, 1 2 (2025): 1-14, doi: 10.311581/JAMDA.2509.1007.1.2.1
VANCOUVER
Kanzi N, Niknam S. Necessary Optimality Conditions for Weakly Efficient Solutions in Convex Multiobjective GSIPs. JAMDA. 2025;1(2):1-14. doi: 10.311581/JAMDA.2509.1007.1.2.1
