Robust Optimization for a Multi-Product Integrated Problem of Planning and Scheduling under Products Uncertainty

Cuiwen  Cao; Mengwen  Chen

doi:10.4236/jamp.2015.31003

Mengwen Chen^*, Cuiwen Cao

Abstract: This paper presents robust optimization models for a multi-product integrated problem of planning and scheduling (based on the work of Terrazas-Moreno & Grossmann (2011) [1]) under products prices uncertainty. With the objective of maximizing the total profit in planning time horizon, the planning section determines the amount of each product, each product distributed to each market, and the inventory level in each manufacturing site during each scheduling time period; the scheduling section determines the products sequence, start and end time of each product running in each production site during each scheduling time period. The uncertainty sets used in robust optimization model are box set, ellipsoidal set, polyhedral set, combined box and ellipsoidal set, combined box and polyhedral set, combined box, ellipsoidal and polyhedral set. The genetic algorithm is utilized to solve the robust optimization models. Case studies show that the solutions obtained from robust optimization models are better than the solutions obtained from the original integrated planning and scheduling 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.

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