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 overheads of state-of-the-art hash-based parallel best-first search algorithms, and show that although Zobrist hashing, the standard hash function used by HDA*, achieves good load balance for many domains, it incurs si...

We propose a computational methodology -"B-LOG"-, which offers the potential for an effective implementation of Logic Programming in a parallel computer. We also propose a weighting scheme to guide the search process through the graph and we apply the concepts of parallel "branch and bound" algorithms in order to perform a "best-first" search using an information theoretic bound. The concept of...

This paper discusses a parallel genetic algorithm (PGA) which focuses on the local operator for Traveling salesman problem (TSP). The local operator is a simple GA named as Local Genetic Algorithm (LGA). The LGA is combined to another GA named as Global Genetic Algorithm (GGA). It increases the computational time running a GA as a local operator in another one. To solve this problem, we build a...

In this paper, a new hybrid conjugate gradient algorithm is proposed for solving unconstrained optimization problems. This new method can generate sufficient descent directions unrelated to any line search. Moreover, the global convergence of the proposed method is proved under the Wolfe line search. Numerical experiments are also presented to show the efficiency of the proposed algorithm, espe...

A parallel inexact Newton method with a line search is proposed for two-stage quadratic stochastic programs with recourse. A lattice rule is used for the numerical evaluation of multi-dimensional integrals, and a parallel iterative method is used to solve the quadratic programming subproblems. Although the objective only has a locally Lipschitz gradient, global convergence and local superlinear...

This paper presents a massively parallel Genetic Algorithm – Pattern Search (GA-PS) with graphics hardware acceleration on bound constrained nonlinear optimization problems. The objective of this study is to determine the effectiveness of using Graphics Processing Units (GPU) as a hardware platform for Genetic Algorithms (GA). The global search of the GA is enhanced by a local Pattern Search (P...

This paper deals with a new algorithm of a parallel simulated annealing HGSA which includes genetic crossover operations. The genetic crossover is used as an enhancement of the origin parallel simulated annealing PSA which allows to recombine solutions produced by individual simulate annealing processes at fixed time intervals. It is found that the proposed algorithm can speed—up the search the...