Resource title

Local search heuristics for single machine scheduling with batching to minimize the number of late jobs

Resource image

image for OpenScout resource :: Local search heuristics for single machine scheduling with batching to minimize the number of late jobs

Resource description

Local search heuristics are developed for a problem of scheduling jobs on a single machine. Jobs are partitioned into families, and a set-up time is necessary when there is a switch in processing jobs from one family to jobs of another family. The objective is to minimize the number of late jobs. Four alternative local search methods are developed: multi-start descent, simulated annealing, tabu search and a genetic algorithm. The performance of these heuristics is evaluated on a large set of test problems. The best results are obtained by the genetic algorithm; multi-start descent also performs quite well

Resource author

Resource publisher

Resource publish date

Resource language

en

Resource content type

application/pdf

Resource resource URL

http://flora.insead.edu/fichiersti_wp/Inseadwp1994/94-45.pdf

Resource license

Copyright INSEAD. All rights reserved