Erik Altman, Jovan Blanusa, et al.
NeurIPS 2023
For hard optimization problems, it is difficult to design heuristic algorithms which exhibit uniformly superior performance for all problem instances. As a result it becomes necessary to tailor the algorithms based on the problem instance. In this paper, we introduce the use of a cooperative problem solving team of heuristics that evolves algorithms for a given problem instance. The efficacy of this method is examined by solving six difficult instances of a bicriteria sparse multiple knapsack problem. Results indicate that such tailored algorithms uniformly improve solutions as compared to using predesigned heuristic algorithms.
Erik Altman, Jovan Blanusa, et al.
NeurIPS 2023
Hannaneh Hajishirzi, Julia Hockenmaier, et al.
UAI 2011
Aditya Malik, Nalini Ratha, et al.
CAI 2024
Hironori Takeuchi, Tetsuya Nasukawa, et al.
Transactions of the Japanese Society for Artificial Intelligence