A class of greedy algorithms for the generalized assignment problem

Romero-Morales, Dolores (1997) A class of greedy algorithms for the generalized assignment problem. In: 16th International Symposium on Mathematical Programming, 24-29 August, 1997, Lausanne, Switzerland.

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Abstract

The Generalized Assignment Problem (GAP) is the problem of finding the minimal cost assignment of jobs to machines such that each job is assigned to exactly one machine, subject to capacity restrictions on the machines. We propose a class of greedy algorithms for the GAP. A family of weight functions is defined to measure a pseudo-cost of assigning a job to a machine. This weight function in turn is used to measure the desirability of assigning each job to each of the machines. The greedy algorithm then schedules jobs according to a decreasing order of desirability. A relationship with the partial solution given by the LP-relaxation of the GAP is found, and we derive conditions under which the algorithm is asymptotically optimal in a probabilistic sense.

Item Type: Conference or Workshop Item (Paper)
Keywords: generalized assignment problem, greedy heuristic, asymptotic feasibility, asymptotic optimality
Subject(s): Management science
Centre: Faculty of Management Science
Date Deposited: 29 May 2012 12:32
Last Modified: 23 Oct 2015 14:07
URI: http://eureka.sbs.ox.ac.uk/id/eprint/3795

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