Improved divine religion algorithm: a novel metaheuristic approach for optimizing electric vehicle routing
Description
Public transportation routing optimization plays a vital role in reducing operational costs and energy consumption, especially with the rise of electric vehicles. However, this problem is inherently NP-hard, making it computationally challenging for traditional optimization methods to solve efficiently, particularly for large-scale scenarios. In this paper, to address this gap, we propose a novel metaheuristic-inspired approach called the Divine Religion Algorithm (DRA). This algorithm draws on societal relations among followers, missionaries, and leaders within a political-ideological framework, offering an innovative evolutionary strategy for optimization. Recognizing the potential for further enhancements, we extended this approach to a more powerful version called DRA-II. This extended version introduces a dynamic reward operator that incentivizes high-performing followers, a penalty operator that discourages underperformers, and a follower migration operator that promotes progressive transformations within the solution units, fostering a competitive and adaptive environment. Our methodology is evaluated within the context of the Electric Vehicle Routing Problem (EVRP), a critical and representative challenge in sustainable transportation planning. The comparative analysis is conducted on medium and large-scale intelligent transportation scenarios, assessing performance through metrics such as "best cost," "average cost," and "standard deviation." Evaluated against Harmony Search, Genetic Algorithm, and Imperialist Competitive Algorithm across 35 instances, DRA-II achieved superior results in small-to-medium-scale scenarios (14.7% cost reduction) with execution times close to GA. Statistical tests (ANOVA, Friedman) confirmed robustness (p < 0.05). DRA-II’s scalability and low standard deviation (Fig. 9) make it viable for real-world logistics. This work advances metaheuristic methods for sustainable transportation.
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Institutions
- Qazvin Islamic Azad UniversityQazvin Province, Qazvin