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
Sala de pinturas


Other papers in the same session


Latest news

  • 1/8/16
    Paper submission is open
  • 1/8/16
    Registration is open

Sponsors

Cookie policy

We use cookies in order to be able to identify and authenticate you on the website. They are necessary for the correct functioning of it, and therefore they can not be disabled. If you continue browsing the website, you are agreeing with their acceptance, as well as our Privacy Policy.

Additionally, we use Google Analytics in order to analyze the website traffic. They also use cookies and you can accept or refuse them with the buttons below.

You can read more details about our Cookie Policy and our Privacy Policy.