dissertation · Monash University · 2023

Enhanced Path Finding Algorithms with Applications in Electric Vehicles

Ahmadi, Saman

Cited by 0Open access

Abstract

The first part of this thesis introduces two solution methods for energy-optimal path finding for Electric Vehicles (EVs). It also develops a complete pickup-and-delivery model with EVs. The second part addresses the key topics of bi-objective and weight constrained path finding. It first presents a new bi-objective search framework that improves the runtime and memory usage of the state of the art by several factors. It then introduces four fast algorithms for the weight constrained shortest path problem and show how our enhanced algorithms can improve the performance over the state of the art by several orders of magnitude.

Cite this paper

APA 7

Ahmadi, S. (2023). Enhanced Path Finding Algorithms with Applications in Electric Vehicles. Monash University. https://doi.org/10.26180/22146194

MLA 9

Ahmadi, Saman. “Enhanced Path Finding Algorithms with Applications in Electric Vehicles.” Monash University, 2023, https://doi.org/10.26180/22146194.

Chicago

Ahmadi, Saman. 2023. “Enhanced Path Finding Algorithms with Applications in Electric Vehicles.” Monash University. https://doi.org/10.26180/22146194.

Harvard

Ahmadi, S. (2023) ‘Enhanced Path Finding Algorithms with Applications in Electric Vehicles’, Monash University. Available at: https://doi.org/10.26180/22146194.

BibTeX

@phdthesis{ahmadi2023enhanced,
  title = {{Enhanced Path Finding Algorithms with Applications in Electric Vehicles}},
  author = {Ahmadi, Saman},
  school = {Monash University},
  year = {2023},
  doi = {10.26180/22146194}
}

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