This paper considers the problem of scheduling the production and distribution activities of a network of plants supplying rapidly perishable materials. The main challenges are (1) addressing simultaneously several interrelated scheduling and routing problems, and (2) finding solutions that take into account the amount of cooperation/ interaction necessary between the various plants. We propose a strategy that combines genetic algorithms and fast schedule construction heuristics for job scheduling and truck routing. The effectiveness of the approach is evaluated against other methods used in industrial practice on a challenging large-scale case study.
Scheduling Production and Distribution of rapidly Perishable Materials with Hybrid GA's / Naso, David; Surico, Michele; Turchiano, Biagio (STUDIES IN COMPUTATIONAL INTELLIGENCE). - In: Evolutionary scheduling: Studies in Computational intelligence / [a cura di] Keshav P. Dahal, Kay Chen Tan, Peter I. Cowling. - STAMPA. - Berlin; Heidelberg : Springer, 2007. - ISBN 978-3-540-48582-7. - pp. 465-483 [10.1007/978-3-540-48584-1_17]
Scheduling Production and Distribution of rapidly Perishable Materials with Hybrid GA's
David Naso;Biagio Turchiano
2007-01-01
Abstract
This paper considers the problem of scheduling the production and distribution activities of a network of plants supplying rapidly perishable materials. The main challenges are (1) addressing simultaneously several interrelated scheduling and routing problems, and (2) finding solutions that take into account the amount of cooperation/ interaction necessary between the various plants. We propose a strategy that combines genetic algorithms and fast schedule construction heuristics for job scheduling and truck routing. The effectiveness of the approach is evaluated against other methods used in industrial practice on a challenging large-scale case study.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
