NDLI: Evolutionary Approaches to Solve an Integrated Lot Scheduling Problem in the Soft Drink Industry

Content Provider	IEEE Xplore Digital Library
Author	Motta Toledo, C.F. Morelato Franca, P. Morabito, R. Kimms, A.
Copyright Year	2007
Description	Author affiliation: Univ. Fed. de Lavras, Lavras (Motta Toledo, C.F.)
Abstract	This paper proposes two evolutionary approaches as procedures to solve the synchronized and integrated two-level lot-sizing and scheduling problem (SITLSP). This problem can be found in some industrial settings, mainly soft drink companies, where the production process involves two interdependent levels with decisions concerning raw material storage and soft drink bottling. The first approach to solve the SITLSP is a multi-population genetic algorithm (GA) with a hierarchical ternary tree structure for populations. The second approach is a memetic algorithm (MA) that extends the GA approach through the inclusion of a local search procedure. The computational study reported reveals that those methods are an effective alternative to solve real-world instances of the SITLSP.
Starting Page	95
Ending Page	100
File Size	399122
Page Count	6
File Format	PDF
DOI	10.1109/HIS.2007.35
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-17
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Job shop scheduling Costs Biological system modeling Production Material storage Computer industry Raw materials Lot sizing Beverage industry Genetic algorithms
Content Type	Text
Resource Type	Article

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