Combining constraint programming and genetic algorithm for dynamic scheduling problems

TitreCombining constraint programming and genetic algorithm for dynamic scheduling problems
Publication TypeConference Paper
Year of Publication2017
AuthorsElkhyari, A, Bellabdaoui, A
Conference Name2017 International Colloquium on Logistics and Supply Chain Management: Competitiveness and Innovation in Automobile and Aeronautics Industries, LOGISTIQUA 2017
Abstract

This paper introduces a new method based on constraint programming (CP) and genetic algorithm (GA) for solving dynamic scheduling problems. The proposed approach allows us to handle scheduling problems with large sizes (i.e. search spaces are too large). Our idea is to break up the search space into disjoined sub-spaces by the genetic algorithm. To each individual of the population is associated a sub-space. Each sub-space is represented by a sub-CSP which is easier to solve than the original scheduling problem. Our first experimentations are addressed to the Endoscopy Unit scheduling in dynamic way. © 2017 IEEE.

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85026635770&doi=10.1109%2fLOGISTIQUA.2017.7962867&partnerID=40&md5=4564dfc4f2b976af00a026b36127e625
DOI10.1109/LOGISTIQUA.2017.7962867
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