Combining simulation with metaheuristics in distributed scheduling problems with stochastic processing times

• Published in: Proceedings - Winter Simulation Conference pp. 2347 - 2357
• Main Authors: Calvet, Laura, Juan, Angel A., Fernandez-Viagas, Victor, Framinan, Jose M.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2016; Winter Simulation Conference (WSC). Proceedings
• Subjects: Algorismes; Algorithms; Algoritmos; centres de producció; centros de producción; Companies; Computational modeling; distribució de probabilitat; distribución de probabilidad; empresa; Job shop scheduling; model computacional; modelo computacional; Probability distribution; problema Job Shop; Production facilities; Random variables; variables aleatorias; variables aleatòries
• ISBN: 1509044868; 9781509044863
• ISSN: 1558-4305; 1558-4305
• DOI: 10.1109/WSC.2016.7822275

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.