85 citations · 104 across the 5 of their papers we have counts for
7 papers
TPAM: A Simulation-Based Model for Quantitatively Analyzing Parameter Adaptation Methods
Ryoji Tanabe, Alex Fukunaga
While a large number of adaptive Differential Evolution (DE) algorithms have been proposed, their Parameter Adaptation Methods (PAMs) are not well understood. We propose a Target f…
Reviewing and Benchmarking Parameter Control Methods in Differential Evolution
Ryoji Tanabe, Alex Fukunaga
Many Differential Evolution (DE) algorithms with various parameter control methods (PCMs) have been proposed. However, previous studies usually considered PCMs to be an integral co…
How Far Are We From an Optimal, Adaptive DE?
Ryoji Tanabe, Alex Fukunaga
We consider how an (almost) optimal parameter adaptation process for an adaptive DE might behave, and compare the behavior and performance of this approximately optimal process to…
A Survey of Parallel A*
Alex Fukunaga, Adi Botea, Yuu Jinnai +1
A* is a best-first search algorithm for finding optimal-cost paths in graphs. A* benefits significantly from parallelism because in many applications, A* is limited by memory usage…
On Hash-Based Work Distribution Methods for Parallel Best-First Search
Yuu Jinnai, Alex Fukunaga
Parallel best-first search algorithms such as Hash Distributed A* (HDA*) distribute work among the processes using a global hash function. We analyze the search and communication o…
Block-Parallel IDA* for GPUs (Extended Manuscript)
Satoru Horie, Alex Fukunaga
We investigate GPU-based parallelization of Iterative-Deepening A* (IDA*). We show that straightforward thread-based parallelization techniques which were previously proposed for m…