L. Escudero, J. F. Monge, D. Romero Morales
We present a modeling framework and a solution approach for a multi-period stochastic mixed 0-1 problem arising in Tactical Supply Chain Planning (TSCP). A scenario tree based scheme is used to represent the parameters' uncertainty and developing the Deterministic Equivalent Model. The cost risk reduction is performed by using a time-consistent expected stochastic dominance risk averse measure. Given the dimensions of this problem in real-life applications, a decomposition approach is proposed. It is based on stochastic dynamic programming (SDP). We computationally compare the performance of plain use of a current stage-of-the.art MIP solver and the proposed SDP approach considering the risk neutral version of the model as the subject for the benchmarking. Additionally, we present computational results obtained by SDP in both versions of the TSCP model, namely using the risk neutral and the risk averse measures.
Keywords: Risk Aversion, Stochastic Dominance, Supply Chain
Scheduled
TD2 Supply Chain Management
May 31, 2016 3:00 PM
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