Strong duality of a conic optimization problem with a single hyperplane and two cone constraints
Sunyoung Kim, Masakazu Kojima

TL;DR
This paper provides a unified geometric framework for understanding strong duality in conic optimization problems with a single hyperplane and two cone constraints, simplifying analysis and revealing conditions for no duality gap.
Contribution
It introduces a reformulation of the problem into a single cone intersection, enabling geometric duality analysis without constraint qualifications.
Findings
Duality gap is absent under geometric conditions.
Reformulation simplifies duality analysis.
Conditions for dual solution existence and boundedness.
Abstract
Strong (Lagrangian) duality of general conic optimization problems (COPs) has long been studied and its profound and complicated results appear in different forms in a wide range of literatures. As a result, characterizing the known and unknown results can sometimes be difficult. The aim of this article is to provide a unified and geometric view of strong duality of COPs for the known results. For our framework, we employ a COP minimizing a linear function in a vector variable subject to a single hyperplane constraint and two cone constraints , . It can be identically reformulated as a simpler COP with the single hyperplane constraint and the single cone constraint . This simple COP and its dual as well as their duality relation can be represented geometrically, and they have no duality gap without any constraint…
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Taxonomy
TopicsAdvanced Optimization Algorithms Research · Optimization and Variational Analysis · Optimization and Mathematical Programming
