Multi-Objective Optimization Using Evolutionary Cuckoo Search Algorithm for Evacuation Planning

Proper emergency evacuation planning is a key to ensuring the safety and efficiency of resources allocation in disaster events. An efficient plan can save human lives avoid other effects disasters. To develop effective plans, this study proposed multi-objective optimization model that assigns individuals shelters through safe routes during available periods. The main objective minimize total travel distance leaving zones shelters, risk on overload shelters. experimental results show Discrete Multi-Objective Cuckoo Search (DMOCS) has better consistent performance as compared standard (MOCS) most cases terms execution time; however, MOCS still within acceptable ranges. Metrics measures such hypervolume indicator, convergence evaluation parameter tuning have been applied evaluate quality Pareto front algorithm. showed DMOCS than MOCS.