Robust Optimization for a Multi-Product Integrated Problem of Planning and Scheduling under Products UncertaintyReport as inadecuate




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This paper presents robust optimizationmodels for a multi-product integrated problem of planning and scheduling basedon the work of Terrazas-Moreno & Grossmann 2011 1 under productsprices uncertainty. With the objective of maximizing the total profit inplanning time horizon, the planning section determines the amount of eachproduct, each product distributed to each market, and the inventory level ineach manufacturing site during each scheduling time period; the schedulingsection determines the products sequence, start and end time of each productrunning in each production site during each scheduling time period. Theuncertainty sets used in robust optimization model are box set, ellipsoidalset, polyhedral set, combined box and ellipsoidal set, combined box andpolyhedral set, combined box, ellipsoidal and polyhedral set. The geneticalgorithm is utilized to solve the robust optimization models. Case studiesshow that the solutions obtained from robust optimization models are betterthan the solutions obtained from the original integrated planning andscheduling when the prices are changed.

KEYWORDS

Uncertainty, Robust Optimization, Integrated Problem of Planning and Scheduling, GA

Cite this paper

Chen, M. and Cao, C. 2015 Robust Optimization for a Multi-Product Integrated Problem of Planning and Scheduling under Products Uncertainty. Journal of Applied Mathematics and Physics, 3, 16-24. doi: 10.4236-jamp.2015.31003.





Author: Mengwen Chen*, Cuiwen Cao

Source: http://www.scirp.org/



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