OPTIMIZING FOGGING AREAS IN DENGUE VECTOR CONTROL STRATEGIES USING GENETIC ALGORITHMS

Wan Nur Afrina Wan Muhammad Azan; Siti Meriam Zahari; S.Sarifah Radiah Shariff; Nurakmal Ahmad Mustafa; Aishah Hani Azil; Ruth Banomyong

Proceedings of ICLT 2025

OPTIMIZING FOGGING AREAS IN DENGUE VECTOR CONTROL STRATEGIES USING GENETIC ALGORITHMS

Wan Nur Afrina Wan Muhammad Azan; Siti Meriam Zahari; S.Sarifah Radiah Shariff; Nurakmal Ahmad Mustafa; Aishah Hani Azil; Ruth Banomyong

Malaysia Institute of Transport (MITRANS), Universiti Teknologi MARA (UiTM), Shah Alam, Malaysia; Malaysia Institute of Transport (MITRANS), Universiti Teknologi MARA (UiTM), Shah Alam, Malaysia; Malaysia Institute of Transport (MITRANS), Universiti Teknologi MARA (UiTM), Shah Alam, Malaysia; Othman Yeop Abdullah Graduate School of Business, Universiti Utara Malaysia, Sintok, Kedah, Malaysia; Department of Parasitology & Medical Entomology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bangi, Malaysia; Center of Excellence in Connectivity, Thammasat Business School, Thammasat University, Bangkok, Thailand

International Conference on Logistics & Transport 2025, Tokyo, Japan, pp. 161-168

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Abstract

Purpose:This study aims to address the persistent challenge of dengue fever in Malaysia, particularly in the context of rapid urbanization and its impact on the rise of vector-borne diseases. It evaluates the effectiveness of different resource allocation strategies in dengue vector control by applying genetic algorithm-based fitness functions to optimize decision-making. This study contributes to the field of public health logistics by demonstrating how algorithmic optimization can improve the strategic deployment of limited resources in urban vector control operations. Design/methodology/approach: A comparative analysis of four fitness functions was conducted using a genetic algorithm framework to simulate resource distribution for dengue control. Fitness Function 1 applies uniform allocation, Fitness Function 2 incorporates severity-based weighting, Fitness Function 3 ranks areas by case counts, and Fitness Function 4 integrates both rank and variability. The performance and impact of each approach were assessed based on allocation efficiency and ability to target high-risk zones. Findings: Results indicate a clear progression in allocation effectiveness from the basic Fitness Function 1 to the more complex Fitness Function 4. While Fitness Functions 2 and 3 show improvements by focusing on severity and case count, respectively, Fitness Function 4 provides the most balanced and strategic allocation. It enhances resource efficiency by accounting for both severity and variab

Keywords

Resource allocation; Dengue vector control; Genetic algorithm; Optimization techniques

Citation

Wan Nur Afrina Wan Muhammad Azan; Siti Meriam Zahari; S.Sarifah Radiah Shariff; Nurakmal Ahmad Mustafa; Aishah Hani Azil; Ruth Banomyong (2025). OPTIMIZING FOGGING AREAS IN DENGUE VECTOR CONTROL STRATEGIES USING GENETIC ALGORITHMS. Proceedings of the International Conference on Logistics & Transport (ICLT 2025), Tokyo, Japan, pp. 161-168.