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Title: Combining simulation with metaheuristics in distributed scheduling problems with stochastic processing times
Author: Calvet Liñan, Laura  
Fernández-Viagas Escudero, Víctor
Framiñán Torre, José Manuel
Juan Pérez, Ángel Alejandro
Keywords: job shop scheduling
random variables
probability distribution
computational modeling
production facilities
Issue Date: Dec-2016
Publisher: Winter Simulation Conference (WSC). Proceedings
Citation: Calvet, L., Fernandez-Viagas, V., Framinan, J.M. & Juan, A.A. (2016). Combining simulation with metaheuristics in distributed scheduling problems with stochastic processing times. Winter Simulation Conference (WSC). Proceedings, 2016(), 2347-2357. doi: 10.1109/WSC.2016.7822275
Published in: Winter Simulation Conference, Washington D.C., EUA, 11-14, desembre de 2016
Project identifier: info:eu-repo/grantAgreement/TRA2013-48180-C3-P
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Abstract: In this paper, we focus on a scenario in which a company or a set of companies conforming a supply network must deliver a complex product (service) composed of several components (tasks) to be processed on a set of parallel flow-shops with a common deadline. Each flow-shop represents the manufacturing of an independent component of the product, or the set of activities of the service. We assume that the processing times are random variables following a given probability distribution. In this scenario, the product (service) is required to be finished by the deadline with a user-specified probability, and the decision-maker must decide about the starting times of each component/task while minimizing one of the following alternative goals: (a) the maximum completion time; or (b) the accumulated deviations with respect to the deadline. A simheuristic-based methodology is proposed for solving this problem, and a series of computational experiments are performed.
Language: English
ISBN: 9781509044863
ISSN: 1558-4305MIAR
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