A Lagrangian dual-based branch-and-bound algorithm for the generalized multi-assignment problem

June S. Park, Byung Ha Lim, Youngho Lee

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

This paper develops a Lagrangian dual-based branch-and-bound algorithm for the generalized multi-assignment problem (GMAP) which includes the well-known generalized assignment problem (GAP) as a special case. In GMAP, an object may be required to be duplicated in multiple locations. We develop a Lagrangian dual ascent algorithm for GMAP. This dual ascent and the subgradient search each possess advantages that can be combined to develop a new Lagrangian dual search algorithm. The latter algorithm, when incorporated into a branch-and-bound algorithm as the lower bounding scheme, can accelerate the search process. Computational results demonstrate the efficiency and robustness of this branch-and-bound algorithm not only for GMAPs, but for GAPs that are more difficult than could be solved by previous algorithms.

Original languageEnglish
Pages (from-to)S271-S282
JournalManagement Science
Volume44
Issue number12 PART 2
DOIs
Publication statusPublished - 1998 Dec

Keywords

  • Generalized Assignment Problem
  • Generalized Multi-Assignment Problem
  • Lagrangian Dual Ascent
  • Lagrangian Dual-Based Branch and Bound
  • Subgradient Search

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research

Fingerprint Dive into the research topics of 'A Lagrangian dual-based branch-and-bound algorithm for the generalized multi-assignment problem'. Together they form a unique fingerprint.

  • Cite this