TITLE:
Robust Optimization for a Multi-Product Integrated Problem of Planning and Scheduling under Products Uncertainty
AUTHORS:
Mengwen Chen, Cuiwen Cao
KEYWORDS:
Uncertainty, Robust Optimization, Integrated Problem of Planning and Scheduling, GA
JOURNAL NAME:
Journal of Applied Mathematics and Physics,
Vol.3 No.1,
January
28,
2015
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.