1,118 research outputs found
Comparative Performance of Tabu Search and Simulated Annealing Heuristics for the Quadratic Assignment Problem
For almost two decades the question of whether tabu search (TS) or simulated
annealing (SA) performs better for the quadratic assignment problem has been
unresolved. To answer this question satisfactorily, we compare performance at
various values of targeted solution quality, running each heuristic at its
optimal number of iterations for each target. We find that for a number of
varied problem instances, SA performs better for higher quality targets while
TS performs better for lower quality targets
A parallel implementation of ant colony optimization
Ant Colony Optimization is a relatively new class of meta-heuristic search techniques for optimization problems. As it is a population-based technique that examines numerous solution options at each step of the algorithm, there are a variety of parallelization opportunities. In this paper, several parallel decomposition strategies are examined. These techniques are applied to a specific problem, namely the travelling salesman problem, with encouraging speedup and efficiency results.Full Tex
A Three-Level Parallelisation Scheme and Application to the Nelder-Mead Algorithm
We consider a three-level parallelisation scheme. The second and third levels
define a classical two-level parallelisation scheme and some load balancing
algorithm is used to distribute tasks among processes. It is well-known that
for many applications the efficiency of parallel algorithms of the second and
third level starts to drop down after some critical parallelisation degree is
reached. This weakness of the two-level template is addressed by introduction
of one additional parallelisation level. As an alternative to the basic solver
some new or modified algorithms are considered on this level. The idea of the
proposed methodology is to increase the parallelisation degree by using less
efficient algorithms in comparison with the basic solver. As an example we
investigate two modified Nelder-Mead methods. For the selected application, a
few partial differential equations are solved numerically on the second level,
and on the third level the parallel Wang's algorithm is used to solve systems
of linear equations with tridiagonal matrices. A greedy workload balancing
heuristic is proposed, which is oriented to the case of a large number of
available processors. The complexity estimates of the computational tasks are
model-based, i.e. they use empirical computational data
Recent Advances in Graph Partitioning
We survey recent trends in practical algorithms for balanced graph
partitioning together with applications and future research directions
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