Contributed Session Mon.2.H 2013

Monday, 13:15 - 14:45 h, Room: H 2013

Cluster 11: Integer & mixed-integer programming [...]

MILP formulations I


Chair: Silvio Alexandre de Araujo



Monday, 13:15 - 13:40 h, Room: H 2013, Talk 1

Laura Mclay
A mixed-integer programming model for enforcing priority list policies in Markov decision processes


Optimal dispatching policies for server-to-customer systems can be identified using Markov decision process models and algorithms, which indicate the optimal server to dispatch to each customer type in each state. Optimal policies are fully state dependent and may be tedious to use in practice. Restricted policies that are partially state dependent and conform to a priority list policy for each type of customer may be easier to use in practice. This research demonstrates how the optimal priority list policy can be identified by formulating constrained Markov decision processes as mixed integer programming models.



Monday, 13:45 - 14:10 h, Room: H 2013, Talk 2

Silvio Alexandre de Araujo
Lagrange heuristic for a reformulated capacitated lot sizing problem in parallel machines

Coauthor: Diego J. Fiorotto


The capacitated lot sizing problem with multiple items, setup time and unrelated parallel machines is considered. The aim of this work is to design a Lagrange heuristic that provides good solutions for this problem and strong lower bounds to assess their quality. Based on a strong reformulations of the problem, Lagrange relaxation is applied on the the demand constraints and the subgradient optimization procedure is used. A primal heuristic, based on production transfers, is developed to generate feasible solutions (upper bounds). Computational experiments are presented on data sets available from the literature.


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