It is essential to develop efficient transportation strategies for the distribution of vital supplies in the aftermath of wide-scale extreme events. While most major cities have importation and distribution plans in place for their communities, the implementation efficacy of these plans is diminished once the transportation network is disrupted following a disaster. This research develops a multi-objective decision model that minimizes cost while maximizing proximity. GIS-style visualization tools are used to create planning scenarios. The methodology also integrates elements from complexity science to control emergent behaviors and cascade failures resulting from interdependent systems failures.