Thecontinuousandincreasinginterestconcerningvectoroptimizationperc- tible in the research community, where contributions dealing with the theory of duality abound lately, constitutes the main motivation that led to writing this book. Decisive was also the research experience of the authors in this ?eld, materialized in a number of works published within the last decade. The need for a book on duality in vector optimization comes from the fact that despite the large amount of papers in journals and proceedings volumes, no book mainly concentrated on this topic was available so far in the scienti?c landscape. There is a considerable presence of books, not all recent releases, on vector optimization in the literature. We mention here the ones due to Chen,HuangandYang(cf. [49]),EhrgottandGandibleux(cf. [65]),Eichfelder (cf. [66]), Goh and Yang (cf. [77]), G.. opfert and Nehse (cf. [80]), G.. opfert, - ahi, Tammer and Z? alinescu (cf. [81]), Jahn (cf. [104]), Kaliszewski (cf. [108]), Luc (cf. [125]), Miettinen (cf. [130]), Mishra, Wang and Lai (cf. [131,132]) and Sawaragi, Nakayama and Tanino (cf. [163]), where vector duality is at most tangentially treated. We hope that from our e?orts will bene? t not only researchers interested in vector optimization, but also graduate and und- graduate students. The framework we consider is taken as general as possible, namely we work in (locally convex) topological vector spaces, going to the usual ?nite - mensional setting when this brings additional insights or relevant connections to the existing literature.

Thecontinuousandincreasinginterestconcerningvectoroptimizationperc- tible in the research community, where contributions dealing with the theory of duality abound lately, constitutes the main motivation that led to writing this book. Decisive was also the research experience of the authors in this ?eld, materialized in a number of works published within the last decade. The need for a book on duality in vector optimization comes from the fact that despite the large amount of papers in journals and proceedings volumes, no book mainly concentrated on this topic was available so far in the scienti?c landscape. There is a considerable presence of books, not all recent releases, on vector optimization in the literature. We mention here the ones due to Chen,HuangandYang(cf. [49]),EhrgottandGandibleux(cf. [65]),Eichfelder (cf. [66]), Goh and Yang (cf. [77]), G.. opfert and Nehse (cf. [80]), G.. opfert, - ahi, Tammer and Z? alinescu (cf. [81]), Jahn (cf. [104]), Kaliszewski (cf. [108]), Luc (cf. [125]), Miettinen (cf. [130]), Mishra, Wang and Lai (cf. [131,132]) and Sawaragi, Nakayama and Tanino (cf. [163]), where vector duality is at most tangentially treated. We hope that from our e?orts will bene? t not only researchers interested in vector optimization, but also graduate and und- graduate students. The framework we consider is taken as general as possible, namely we work in (locally convex) topological vector spaces, going to the usual ?nite - mensional setting when this brings additional insights or relevant connections to the existing literature.

The results presented in this book originate from the last decade research work of the author in the ?eld of duality theory in convex optimization. The reputation of duality in the optimization theory comes mainly from the major role that it plays in formulating necessary and suf?cient optimality conditions and, consequently, in generatingdifferent algorithmic approachesfor solving mathematical programming problems. The investigations made in this work prove the importance of the duality theory beyond these aspects and emphasize its strong connections with different topics in convex analysis, nonlinear analysis, functional analysis and in the theory of monotone operators. The ?rst part of the book brings to the attention of the reader the perturbation approach as a fundamental tool for developing the so-called conjugate duality t- ory. The classical Lagrange and Fenchel duality approaches are particular instances of this general concept. More than that, the generalized interior point regularity conditions stated in the past for the two mentioned situations turn out to be p- ticularizations of the ones given in this general setting. In our investigations, the perturbationapproachrepresentsthestartingpointforderivingnewdualityconcepts for several classes of convex optimization problems. Moreover, via this approach, generalized Moreau-Rockafellar formulae are provided and, in connection with them, a new class of regularity conditions, called closedness-type conditions, for both stable strong duality and strong duality is introduced. By stable strong duality we understand the situation in which strong duality still holds whenever perturbing the objective function of the primal problem with a linear continuous functional.