A bottleneck Steiner tree based multi-objective location model and intelligent optimization of emergency logistics systems

Logistics networks could be very fragile in a global environment due to unexpected emergencies such as earthquakes, tsunamis and terrorists attacks. Therefore, the research on emergency logistics systems is extremely significant. The dynamic changes, quick responses and unpredictable events are main features of the location problems in emergency logistics systems, which make them quite different from the traditional logistics networks. The previous single-objective location models and solution algorithms do not capture the new characteristics that arise from the emergency logistics systems. This paper first proposes a new node-weighted bottleneck Steiner tree based multi-objective location optimization model for the emergency logistics systems. Then, a cellular stochastic diffusion search based intelligent algorithm is introduced to solve the proposed model. Under different emergent scenarios, several examples are used to illustrate the application of the proposed model. Numerical experiments show that the proposed approach is effective and efficient for solving the location problem of emergency logistics systems.

► We establish a new bottleneck Steiner tree based multi-objective location optimization model.
► We present a stochastic diffusion search based intelligent algorithm for finding a set of Pareto-optimal solutions.
► The effect of the proposed method for different scenarios is analyzed.