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【MBA中國網(wǎng)訊】

Logistics Network Design and Facility Location: The value of a multi-period stochastic solution

物流網(wǎng)絡設計與設施選址：多周期隨機解決方案的價值

講座時間：9月12日（周四）9：00

講座地點：25樓A區(qū)3A教室

主講人：Francisco Saldanha da Gama

主講人介紹：

Francisco Saldanha da Gama是里斯本大學理學院統(tǒng)計與運籌學系運籌學教授。他在國際期刊上發(fā)表了大量論文，主要涉及的領域有選址分析，供應鏈管理，物流和組合優(yōu)化等領域。他的論文"Facility location and supply chain management---A review"獲得了歐洲區(qū)EJOR最佳評審論文獎（2012年）和Elsevier的EJOR最高被引文章將2007--2011（2012）。目前，他是

講座內容:

In the past decades logistics network design has been a very active research field. This is an area where facility location and logistics are strongly intertwined, which is explained by the fact that many researchers working in Logistics address very often location problems as part of the strategic/tactical logistics decisions.

Despite all the work done, the economic globalization together with the emergence of new technologies and communication paradigms are posing new challenges when it comes to developing optimization models for supporting decision making in this area. Dealing with time and uncertainty has become unavoidable in many situations.

In this presentation, different modeling aspects related with the inclusion of time and uncertainty in facility location problems are discussed. The goal is to better understand problems that are at the core of more comprehensive ones in logistics network design. By considering time explicitly in the models it becomes possible to capture some features of practical relevance that cannot be appropriately captured in a static setting; by considering a stochastic modeling framework it is possible to build risk-aware models.

Unfortunately, the resulting models are often too large and thus hard to tackle even when using specially tailored procedures. This raises a query: is there a clear gain when considering a more involved model instead of a simplified one (e.g. deterministic or static)? In search for an answer to this question, several measures are discussed that include the value of a multiperiod solution and the value of a risk-aware solution