On the time-consistent stochastic dominance risk averse measure for tactical supply chain planning under uncertainty
In this work a modeling framework and a solution approach have been presented for a multi-period stochastic mixed 0–1 problem arising in tactical supply chain planning (TSCP). A multistage scenario tree based scheme is used to represent the parameters’ uncertainty and develop the related Determinist...
| Authors: | , , |
|---|---|
| Format: | article |
| Publication Date: | 2017 |
| Country: | España |
| Institution: | Universidad Miguel Hernández de Elche |
| Repository: | REDIUMH. Depósito Digital de la UMH |
| OAI Identifier: | oai:dspace.umh.es:11000/6118 |
| Online Access: | http://hdl.handle.net/11000/6118 |
| Access Level: | Open access |
| Keyword: | Tactical supply chain planning Nonlinear separable objective function Multistage stochastic integer optimization Risk management Time-consistency Stochastic nested decomposition 519.1 - Teoría general del análisis combinatorio. Teoría de grafos |
| Summary: | In this work a modeling framework and a solution approach have been presented for a multi-period stochastic mixed 0–1 problem arising in tactical supply chain planning (TSCP). A multistage scenario tree based scheme is used to represent the parameters’ uncertainty and develop the related Deterministic Equivalent Model. A cost risk reduction is performed by using a new time-consistent 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). The computational experience is twofold, a compar- ison is performed between the plain use of a current state-of-the-art mixed integer optimization solver and the proposed SDP decomposition approach considering the risk neutral version of the model as the subject for the benchmarking. The add-value of the new risk averse strategy is confirmed by the compu- tational results that are obtained using SDP for both versions of the TSCP model, namely, risk neutral and risk averse. |
|---|