An Enhancement of Cuckoo Search Algorithm for Optimal Earthquake Evacuation Space Allocation in Intramuros, Manila City

TL;DR

This paper introduces an Enhanced Cuckoo Search Algorithm (ECSA) that improves initial population diversity and parameter tuning, leading to better optimization performance, demonstrated on benchmark functions and applied to earthquake evacuation planning in Manila.

Contribution

The paper proposes an enhanced version of CSA using Sobol sequences and Cosine Annealing with Warm Restarts, significantly improving optimization results over the standard CSA.

Findings

ECSA outperforms CSA on 11 of 13 benchmark functions with 30% average fitness improvement.

ECSA achieves 35% better results on unimodal and 24% on multimodal functions.

ECSA demonstrates increased convergence efficiency in solving complex optimization problems.

Abstract

The Cuckoo Search Algorithm (CSA), while effective in solving complex optimization problems, faces limitations in random population initialization and reliance on fixed parameters. Random initialization of the population often results in clustered solutions, resulting in uneven exploration of the search space and hindering effective global optimization. Furthermore, the use of fixed values for discovery rate and step size creates a trade-off between solution accuracy and convergence speed. To address these limitations, an Enhanced Cuckoo Search Algorithm (ECSA) is proposed. This algorithm utilizes the Sobol Sequence to generate a more uniformly distributed initial population and incorporates Cosine Annealing with Warm Restarts to dynamically adjust the parameters. The performance of the algorithms was evaluated on 13 benchmark functions (7 unimodal, 6 multimodal). Statistical analyses were conducted to determine the significance and consistency of the results. The ECSA outperforms the CSA in 11 out of 13 benchmark functions with a mean fitness improvement of 30% across all functions, achieving 35% for unimodal functions and 24% for multimodal functions. The enhanced algorithm demonstrated increased convergence efficiency, indicating its superiority to the CSA in solving a variety of optimization problems. The ECSA is subsequently applied to optimize earthquake evacuation space allocation in Intramuros, Manila.