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Solving multiple objective quasi‐convex goal programming problems by linear programming
Author(s) -
Li HL.,
Yu CS.
Publication year - 2000
Publication title -
international transactions in operational research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.032
H-Index - 52
eISSN - 1475-3995
pISSN - 0969-6016
DOI - 10.1111/j.1475-3995.2000.tb00198.x
Subject(s) - mathematical optimization , linear programming , convex optimization , fractional programming , convex analysis , operator (biology) , convex function , proper convex function , regular polygon , mathematics , linear matrix inequality , second order cone programming , computer science , convex combination , nonlinear programming , nonlinear system , quantum mechanics , biochemistry , chemistry , physics , geometry , repressor , transcription factor , gene
This study presents a novel means of resolving multiple objective goal programming (GP) problems with quasi‐convex linear penalty functions. The proposed method initially expresses a quasi‐convex function by the maximum operator of two convex functions, then solves it via a linear programming technique. The proposed method does not contain any zero–one variables; nor does it require dividing the multi‐objective quasi‐convex GP problem into large sub‐problems as in conventional methods. Some illustrative examples are provided.