Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

A Branch-and-Price Algorithm for the Multilevel Generalized Assignment Problem

Alberto Ceselli and Giovanni Righini
Operations Research
Vol. 54, No. 6 (Nov. - Dec., 2006), pp. 1172-1184
Published by: INFORMS
Stable URL: http://www.jstor.org/stable/25147045
Page Count: 13
  • Download ($30.00)
  • Cite this Item
A Branch-and-Price Algorithm for the Multilevel Generalized Assignment Problem
Preview not available

Abstract

The multilevel generalized assignment problem (MGAP) is a variation of the generalized assignment problem, in which agents can execute tasks at different efficiency levels with different costs. We present a branch-and-price algorithm that is the first exact algorithm for the MGAP. It is based on a decomposition into a master problem with set-partitioning constraints and a pricing subproblem that is a multiple-choice knapsack problem. We report on our computational experience with randomly generated instances with different numbers of agents, tasks, and levels; and with different correlations between cost and resource consumption for each agent-task-level assignment. Experimental results show that our algorithm is able to solve instances larger than those of the maximum size considered in the literature to proven optimality.

Page Thumbnails

  • Thumbnail: Page 
1172
    1172
  • Thumbnail: Page 
1173
    1173
  • Thumbnail: Page 
1174
    1174
  • Thumbnail: Page 
1175
    1175
  • Thumbnail: Page 
1176
    1176
  • Thumbnail: Page 
1177
    1177
  • Thumbnail: Page 
1178
    1178
  • Thumbnail: Page 
1179
    1179
  • Thumbnail: Page 
1180
    1180
  • Thumbnail: Page 
1181
    1181
  • Thumbnail: Page 
1182
    1182
  • Thumbnail: Page 
1183
    1183
  • Thumbnail: Page 
1184
    1184