Fast multi-objective scheduling of jobs to constrained resources using a hybrid evolutionary algorithm

Abstract

The problem tackled here combines three properties of scheduling tasks, each of which makes the basic task more challenging: job scheduling with precedence rules, co-allocation of restricted resources of different performances and costs, and a multi-objective fitness function. As the algorithm must come up with results within a few minutes runtime, EA techniques must be tuned to this limitation. The paper describes how this was achieved and compares the results with a common scheduling algorithm, the Giffler-Thompson procedure. © 2008 Springer-Verlag Berlin Heidelberg.