The Hybrid of WOABAT-IFDO Optimization Algorithm and Its Application in Crowd Evacuation Simulation

• Main Authors: Hamizan, Sharbini, Roselina, Sallehuddin, Habibollah, Haron
• Format: Proceeding
• Language: English
• Published: 2023
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://ir.unimas.my/id/eprint/41789/1/The%20Hybrid%20of%20WOABAT-IFDO.pdf; http://ir.unimas.my/id/eprint/41789/; https://link.springer.com/chapter/10.1007/978-981-19-8406-8_49
• Institution: Universiti Malaysia Sarawak

This paper proposes a new hybrid of nature inspired optimization algorithm (IFDO-WOABAT) based on the latest optimization algorithm namely Improved Fitness Dependent Optimization (IFDO) with Whale-Bat Optimization algorithm (WOABAT). The hybrid is essential to overcome the inaccuracy in searching optimal path when dealing with many agents in conjunction with exploration and exploitation element in WOABAT signify the process of searching behaviour and optimizing the speed value of agent. The performance of the new hybrid optimization algorithm is verified using standard classical test function and further evaluated with other four renowned optimization algorithms and the results showed that it is better in most cases compared with the existing algorithms. Ultimately, the algorithm’s performance also has been tested in crowd simulation evacuation that involves a different number of agents and with/without obstacle scenario. The conducted experiment reveals promising results and signify effectiveness in minimizing the evacuation time.