Robust goal programming approach to an intermodal routing decision problem

Abstract

Under fierce competition for today business, it is very important for companies to reduce their logistic cost. Intermodal transport can exploit transportation cost structure and gain service response. Selecting transportation routes under various factors such as minimum transportation cost, just-in-time commitment, and transit time variability is a crucial decision. Unlike traditional model assumption, uncertainty for data collection in each parameter is presented. In this paper, the intermodal transportation problem is formulated as a robust goal programming to address data uncertainty in transit time variability. The numerical result was tested against tapioca transportation network in Thailand.