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- Doug Hains, Zach Cashero, Mark Ottenberg, Wim Bohm, Sanjay V. Rajopadhye
- 2011 IEEE International Symposium on Parallel and…
- 2011

CUDASW++ is a parallelization of the Smith-Waterman algorithm for CUDA graphical processing units that computes the similarity scores of a query sequence paired with each sequence in a database. The algorithm uses one of two kernel functions to compute the score between a given pair of sequences: the inter-task kernel or the intra-task kernel. We have… (More)

- Thang N Bui, ThanhVu Nguyen, +43 authors Xin Yao
- 2009

- L. Darrell Whitley, Doug Hains, Adele E. Howe
- GECCO
- 2009

A new recombination operator is introduced for the Traveling Salesman Problem called <i>partition crossover</i>. Theoretical and empirical results indicate that when two local optima are recombined using partition crossover, two offspring are produced that are highly likely to also be local optima. Thus, the operator is capable of jumping or… (More)

- L. Darrell Whitley, Doug Hains, Adele E. Howe
- PPSN
- 2010

We present a hybrid Genetic Algorithm that incorporates the Generalized Partition Crossover (GPX) operator to produce an algorithm that is competitive with the state of the art for the Traveling Salesman Problem (TSP). GPX is respectful, transmits alleles and is capable of tunneling directly to new local optima. Our results show that the Hybrid Genetic… (More)

- Doug Hains, L. Darrell Whitley, Adele E. Howe
- JORS
- 2011

The solution space of the travelling salesman problem under 2-opt moves has been characterized as having a big-valley structure, in which the evaluation of a tour is positively correlated to the distance of the tour from the global optimum. We examine the big-valley hypothesis more closely and show that while the big-valley structure does appear in much of… (More)

- Wenxiang Chen, L. Darrell Whitley, Doug Hains, Adele E. Howe
- GECCO
- 2013

Local search methods based on explicit neighborhood enumeration require at least $O(n)$ time to identify all possible improving moves. For k-bounded pseudo-Boolean optimization problems, recent approaches have achieved $O(k^2*2^{k})$ runtime cost per move, where $n$ is the number of variables and $k$ is the number of variables per subfunction. Even though… (More)

- L. Darrell Whitley, Adele E. Howe, Doug Hains
- AAAI
- 2013

Stochastic local search (SLS) is the dominant paradigm for incomplete SAT and MAXSAT solvers. Early studies on small 3SAT instances found that the use of " best improving " moves did not improve search compared to using an arbitrary " first improving " move. Yet SLS algorithms continue to use best improving moves. We revisit this issue by studying very… (More)

- Doug Hains, L. Darrell Whitley, Adele E. Howe, Wenxiang Chen
- GECCO
- 2013

By converting the MAXSAT problem to Walsh polynomials, we can efficiently and exactly compute the hyperplane averages of fixed order <i>k</i>. We use this fact to construct initial solutions based on variable configurations that maximize the sampling of hyperplanes with good average evaluations. The Walsh coefficients can also be used to implement a… (More)

- Doug Hains, L. Darrell Whitley, Adele E. Howe
- PPSN
- 2012

Multi-trial Lin-Kernighan-Helsgaun 2 (LKH-2) is widely considered to be the best Interated Local Search heuristic for the Traveling Salesman Problem (TSP) and has found the best-known solutions to a large number of benchmark problems. Although LKH-2 performs exceptionally well on most instances, it is known to have difficulty on clustered instances of the… (More)