Canonical dual approach to solving 0-1 quadratic programming problems

Shu Cherng Fang, David Yang Gao, Ruey Lin Sheu, Soon Yi Wu

Research output: Contribution to journalArticlepeer-review

56 Citations (Scopus)

Abstract

By using the canonical dual transformation developed recently, we derive a pair of canonical dual problems for 0-1 quadratic programming problems in both minimization and maximization form. Regardless convexity, when the canonical duals are solvable, no duality gap exists between the primal and corresponding dual problems. Both global and local optimality conditions are given. An algorithm is presented for finding global minimizers, even when the primal objective function is not convex. Examples are included to illustrate this new approach.

Original languageEnglish
Pages (from-to)125-142
Number of pages18
JournalJournal of Industrial and Management Optimization
Volume4
Issue number1
DOIs
Publication statusPublished - 2008

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Strategy and Management
  • Control and Optimization
  • Applied Mathematics

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