Generalized best-first search strategies and the optimality of A*
Journal of the ACM (JACM)
Evolutionary Algorithms: The Role of Mutation and Recombination
Evolutionary Algorithms: The Role of Mutation and Recombination
Using Genetic Algorithms to Solve NP-Complete Problems
Proceedings of the 3rd International Conference on Genetic Algorithms
A shortest path algorithm with novel heuristics for dynamic transportation networks
International Journal of Geographical Information Science
Models of Greedy Algorithms for Graph Problems
Algorithmica
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In this paper we consider the concept of functional paths through network datasets. Functional paths are paths that may be suboptimal in terms of cumulative edge weight, but in which the morphology of the route may serve a specific functional purpose (e.g., detection avoidance). Such routes may tend toward optimal in terms of minimizing for edge weight, but not at the expense of the functional purpose of the route. We present this class of routing problems and illustrate how evolutionary approaches used in conjunction with more traditional graph-based computation offers a great deal of flexibility in finding feasible solutions. Using both synthetic graphs and real-world road networks, we present a hybrid evolutionary and graph-based approach for discovering routes with specific functional characteristics. The presented evolutionary algorithm represents a novel solution to a challenging class of problems not readily solved by more traditional approaches.