This paper formulates and solves a lane-based evacuation network optimization problem that integrates lane reversal and crossing elimination strategies. To tackle the combinatorial complexity arising from this combined treatment of discrete network capacity and connectivity settings, an integrated Lagrangian relaxation and tabu search solution method is developed. The method takes advantage of Lagrangian relaxation for problem decomposition and complexity reduction while its algorithmic logic is designed based on the principles of tabu search. Numerical results from optimizing a regional evacuation network for a nuclear power plant illustrate the validness and usefulness of the modeling and solution methodology in evacuation planning practice. (A) Reprinted with permission from Elsevier.
Abstract