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A modified coronavirus herd immunity optimizer for capacitated vehicle routing problem
Lamees Mohammad Dalbah1, Mohammed Azmi Al-Betar1,2, Mohammed A Awadallah3,4
1Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman, United Arab Emirates.
Journal of King Saud University. Computer and Information Sciences
|July 31, 2023
Summary
A modified Coronavirus Herd Immunity Optimizer (CHIO) effectively solves the capacitated vehicle routing problem (CVRP). This metaheuristic algorithm demonstrates competitive results on complex datasets, offering efficient routing solutions.
Area of Science:
- Operations Research
- Computer Science
- Optimization Algorithms
Background:
- The Capacitated Vehicle Routing Problem (CVRP) is an NP-hard optimization challenge.
- Metaheuristic algorithms are commonly employed to address the complexity of CVRP.
- The Coronavirus Herd Immunity Optimizer (CHIO) is a novel population-based metaheuristic algorithm.
Purpose of the Study:
- To modify the CHIO algorithm for efficient solution of the CVRP.
- To evaluate the performance of the modified CHIO on benchmark CVRP datasets.
- To compare the modified CHIO against existing state-of-the-art algorithms.
Main Methods:
- Modification of CHIO operators to ensure solution feasibility for CVRP.
- Testing the modified CHIO on synthetic CVRP models and the ABEFMP dataset.
- Comparative analysis of modified CHIO results with 13 other algorithms.
Main Results:
- Modified CHIO achieved comparable results on 2 out of 10 synthetic instances.
- The algorithm provided acceptable results for the remaining synthetic instances.
- On the more complex ABEFMP dataset, modified CHIO achieved highly competitive results, ranking first in 8 out of 27 instances.
Conclusions:
- The modified CHIO algorithm is an efficient method for solving the CVRP.
- This approach shows promise for application to other vehicle routing problems, including the multiple traveling salesman problem.
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