incorporating sustainability in temporary shelter distribution for disaster response by the lp-based nsga-ii

This paper introduces a comprehensive response mechanism designed to distribute temporary shelters after significant disasters effectively. the primary goal of this system is to overcome challenges posed by coordination, logistics, and resource allocation constraints to optimize relief operations following a catastrophe. the model utilizes a linear programming (lp) metric and a non-dominated sorting genetic algorithm (nsga-ii) as a well-known multi-objective evolutionary algorithm for advanced optimization. by leveraging these methodologies, the model validates its effectiveness while considering multiple objective functions and incorporating sustainability using a response perspective. the findings of the study verify the model's success in enhancing post-disaster shelter distribution and an overall responsive approach in various dimensional scenarios. the proposed integrated system can substantially contribute to the recovery of the impacted regions by streamlining coordination and improving the efficiency of relief operations in a more organized way. it provides valuable insights for decision-makers, practitioners, and researchers involved in disaster management. finally, a conclusion and further research are provided.