The project aims to adapt and apply hyperheuristic methods for automatically generating heuristics to solve electric vehicle routing problems. As conventional vehicles with internal combustion engines are phased out in favor of electric vehicles to reduce harmful emissions, a new need arises to address the intricacies of electric vehicle routing. This problem, known as NP-hard, is commonly tackled using heuristic methods, particularly for larger or dynamically changing scenarios. However, due to its complexity, manually crafting effective heuristics proves challenging. Thus, the motivation lies in leveraging hyperheuristic methods to automate this process and generate suitable heuristics tailored to electric vehicle routing.
The project seeks to explore various hyperheuristic methods and their adaptations to develop heuristics for solving electric vehicle routing problems. It will also investigate opportunities to improve the efficiency of these methods and adapt them to different variations of electric vehicle routing challenges. The ultimate goal is to demonstrate the applicability of the proposed hyperheuristic methods across various scenarios, particularly those mirroring real-world logistics problems, while considering the unique challenges and constraints posed by electric vehicles.
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