Optimization on Emergency Resources Transportation Network Based on Bayes Risk Function: A Case Study

Abstract EN

In order to coordinate the complex relationship between supplies distribution and path selection, some influential factors must be taken into account such as the insufficient remaining capacity of the road and uncertainty of travel time during supplies distribution and transportation.

After the structure of emergency logistics network is analyzed, the travel time Bayes risk function of path and the total loss Bayes risk function of the disaster area are proposed.

With the emergency supplies total transportation unit loss as the goal, an emergency logistics network optimization model under crowded conditions is established by the Bayes decision theory and solved by the improved ant colony algorithm.

Then, a case of the model is validated to prove that the emergency logistics network optimization model is effective in congested conditions.