- Generalized Goal Programming: Polynomial Methods and Applications Emilio Carrizosa (ecarrizcica.es) Joerg Fliege (fliegemath.uni-dortmund.de) Abstract: In this paper we address a general Goal Programming problem with linear objectives, convex constraints, and an arbitrary componentwise nondecreasing norm to aggregate deviations with respect to targets. In particular, classical Linear Goal Programming problems, as well as several models in Location and Regression Analysis are modeled within this framework. In spite of its generality, this problem can be analyzed from a geometrical and a computational viewpoint, and a unified solution methodology can be given. Indeed, a dual is derived, enabling us to describe the set of optimal solutions geometrically. Moreover, Interior-Point methods are described which yield an $\varepsilon$-optimal solution in polynomial time. Keywords: Goal Programming, Closest points, Interior point methods, Location, Regression. Category 1: Other Topics (Multi-Criteria Optimization ) Category 2: Convex and Nonsmooth Optimization (Convex Optimization ) Category 3: Applications -- OR and Management Sciences (Other ) Citation: UNPUBLISHED. INSTITUTION = {Vakgroep Beleidsinformatica, Department of Management Informatics, Vrije Universiteit Brussel}, YEAR = 1999, NUMBER = {BEIF/108}, ADDRESS = {Pleinlaan 2, B-1050 Brussel, Belgium}, MONTH = {January} Download: [Postscript][PDF]Entry Submitted: 01/19/2001Entry Accepted: 01/19/2001Entry Last Modified: 01/19/2001Modify/Update this entry Visitors Authors More about us Links Subscribe, Unsubscribe Digest Archive Search, Browse the Repository Submit Update Policies Coordinator's Board Classification Scheme Credits Give us feedback Optimization Journals, Sites, Societies Optimization Online is supported by the Mathematical Programming Society and by the Optimization Technology Center.