Convex composite multi-objective nonsmooth programming

V. Jeyakumar, Xiaoqi Yang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

33 Citations (Scopus)


This paper examines nonsmooth constrained multi-objective optimization problems where the objective function and the constraints are compositions of convex functions, and locally Lipschitz and Gâteaux differentiable functions. Lagrangian necessary conditions, and new sufficient optimality conditions for efficient and properly efficient solutions are presented. Multi-objective duality results are given for convex composite problems which are not necessarily convex programming problems. Applications of the results to new and some special classes of nonlinear programming problems are discussed. A scalarization result and a characterization of the set of all properly efficient solutions for convex composite problems are also discussed under appropriate conditions.
Original languageEnglish
Pages (from-to)325-343
Number of pages19
JournalMathematical Programming
Issue number1-3
Publication statusPublished - 1 Mar 1993
Externally publishedYes


  • Composite functions
  • multi-objective problems
  • necessary and sufficient conditions
  • nonsmooth programming
  • scalarizations

ASJC Scopus subject areas

  • Software
  • Mathematics(all)


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