Pivot rules for linear programming: A survey on recent theoretical developments

Tamás Terlaky, Shuzhong Zhang

Research output: Contribution to journalArticlepeer-review

78 Scopus citations

Abstract

The purpose of this paper is to discuss the various pivot rules of the simplex method and its variants that have been developed in the last two decades, starting from the appearance of the minimal index rule of Bland. We are mainly concerned with finiteness properties of simplex type pivot rules. Well known classical results concerning the simplex method are not considered in this survey, but the connection between the new pivot methods and the classical ones, if there is any, is discussed. In this paper we discuss three classes of recently developed pivot rules for linear programming. The first and largest class is the class of essentially combinatorial pivot rules including minimal index type rules and recursive rules. These rules only use labeling and signs of the variables. The second class contains those pivot rules which can actually be considered as variants or generalizations or specializations of Lemke's method, and so they are closely related to parametric programming. The last class has the common feature that the rules all have close connections to certain interior point methods. Finally, we mention some open problems for future research.

Original languageEnglish (US)
Pages (from-to)203-233
Number of pages31
JournalAnnals of Operations Research
Volume46-47
Issue number1
DOIs
StatePublished - Mar 1 1993

Keywords

  • Linear programming
  • cycling
  • minimal index rule
  • parametric programming
  • pivot rules
  • recursion
  • simplex method

Fingerprint Dive into the research topics of 'Pivot rules for linear programming: A survey on recent theoretical developments'. Together they form a unique fingerprint.

Cite this