Optimality conditions in convex multiobjective SIP
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http://hdl.handle.net/10045/67476
Title: | Optimality conditions in convex multiobjective SIP |
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Authors: | Goberna, Miguel A. | Kanzi, Nader |
Research Group/s: | Laboratorio de Optimización (LOPT) |
Center, Department or Service: | Universidad de Alicante. Departamento de Matemáticas |
Keywords: | Multi-objective and goal programming | Optimality conditions, duality | Convex programming |
Knowledge Area: | Estadística e Investigación Operativa |
Issue Date: | Jul-2017 |
Publisher: | Springer Berlin Heidelberg |
Citation: | Mathematical Programming. 2017, 164(1): 167-191. doi:10.1007/s10107-016-1081-8 |
Abstract: | The purpose of this paper is to characterize the weak efficient solutions, the efficient solutions, and the isolated efficient solutions of a given vector optimization problem with finitely many convex objective functions and infinitely many convex constraints. To do this, we introduce new and already known data qualifications (conditions involving the constraints and/or the objectives) in order to get optimality conditions which are expressed in terms of either Karusk–Kuhn–Tucker multipliers or a new gap function associated with the given problem. |
Sponsor: | This research was partially cosponsored by the Ministry of Economy and Competitiveness (MINECO) of Spain, and by the European Regional Development Fund (ERDF) of the European Commission, Project MTM2014-59179-C2-1-P. |
URI: | http://hdl.handle.net/10045/67476 |
ISSN: | 0025-5610 (Print) | 1436-4646 (Online) |
DOI: | 10.1007/s10107-016-1081-8 |
Language: | eng |
Type: | info:eu-repo/semantics/article |
Rights: | © Springer-Verlag Berlin Heidelberg and Mathematical Optimization Society 2016 |
Peer Review: | si |
Publisher version: | http://dx.doi.org/10.1007/s10107-016-1081-8 |
Appears in Collections: | INV - LOPT - Artículos de Revistas |
Files in This Item:
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2017_Goberna_Kanzi_MathProgramSerA_final.pdf | Versión final (acceso restringido) | 399,4 kB | Adobe PDF | Open Request a copy |
2017_Goberna_Kanzi_MathProgramSerA_preprint.pdf | Preprint (acceso abierto) | 1,1 MB | Adobe PDF | Open Preview |
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