[QGK18a] Valid inequalities for solving a stochastic lot-sizing problem with returns
Conférence Internationale avec comité de lecture :
ISMP,
July 2018,
France,
motcle:
Résumé:
We seek to plan production activities on a re-manufacturing
system over a multi-period horizon. The system comprises
three processes; disassembly, refurbishing and reassembly.
Uncertainties are assumed on the quality and quantity of re-
turned products, customers demand and production costs.
This leads to a multi-echelon stochastic lot-sizing problem
with product returs and lost sales minimizing the total ex-
pected production costs. We propose a multi-stage stochastic
integer programming approach relying on a scenario tree to
represent the uncertain information structure, resulting in the
formulation of a large-size MILP. New valid tree inequalities
are obtained by mixing previously known path inequalities.
They are used in a Branch-and-Cut framework to solve the
problem. Computational results will illustrate the effectivness
of the proposed method. The number of instances solved to
optimality is increased by a factor of 1.8 as compared to the
use of the commercial solver CPLEX.