A parallel hybrid genetic algorithm-simulated annealing for solving Q3AP on computational grid

Loukil, Lakhdar; Mehdi, Malika; Melab, Nouredine; Talbi, El‐Ghazali; Bouvry, Pascal

doi:10.1109/ipdps.2009.5161126

Cited by 13 publications

(14 citation statements)

References 23 publications

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“…Finally, in [19] we proposed a hybrid meta-heuristic for the Q3AP combining a GA and a simulated annealing (SA) algorithm. Different parallel models were used and compared in a grid environment.…”

Section: B Related Work On Q3apmentioning

confidence: 99%

Interval-based initialization method for permutation-based problems

Mehdi

Melab

Talbi

et al. 2010

IEEE Congress on Evolutionary Computation

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When dealing with exponential search spaces and when no special knowledge is available on global optima, initial populations for population-based meta-heuristics should be uniformly distributed on the search space in order to sample basins of attraction of all local optima. In this paper, we propose a new initialization strategy for permutation problems. The new method is based on an original tree representation of the search space. Such representation was previously used for exact methods but never for meta-heuristics. The proposed method has been tested using a parallel Genetic Algorithm implemented in the ParadisEO framework and experimented on the Nationwide Grid5000 experimental grid using the Q3AP (3D QAP) permutation problem. The preliminary results are promising.

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Section: B Related Work On Q3apmentioning

confidence: 99%

Interval-based initialization method for permutation-based problems

Mehdi

Melab

Talbi

et al. 2010

IEEE Congress on Evolutionary Computation

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“…In comparison with the literature [4], [9], the obtained results by the ILS-TS with our proposed neighborhood are really competitive. Indeed, considering a smaller number of maximal evaluations (thus less computational time), this algorithm is able to find the optimal/best known value with a better significant rate success (varying from 62% to 100%) for most Nugent instances.…”

Section: B Effectiveness In Comparison With the Literaturementioning

confidence: 61%

“…Indeed, If the neighborhood structure is not adequate to the problem, any LS metaheuristic will fail to solve the problem. Regarding the Q3AP, a basic neighborhood for LS algorithms has been proposed in [8] and investigated in different works of the literature [4], [9]. This neighborhood is based on the Q3AP permutation-based formulation (4) where each generated solution is obtained by an exchange of two positions in either the first permutation p or the second q.…”

Section: Local Search Neighborhoods For the Q3ap A Formalizatiomentioning

confidence: 99%

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A GPU-based iterated tabu search for solving the quadratic 3-dimensional assignment problem

Loukil

Melab

Talbi

2010

ACS/IEEE International Conference on Computer Systems and Applications - AICCSA 2010

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Abstract-The quadratic 3-dimensional assignment problem (Q3AP) is an extension of the well-known NP-hard quadratic assignment problem. It has been proved to be one of the most difficult combinatorial optimization problems. Local search (LS) algorithms are a class of heuristics which have been successfully applied to solve such hard optimization problem. These methods handle with a single solution iteratively improved by exploring its neighborhood in the solution space. In this paper, we propose an iterated tabu search for solving the Q3AP. The design of this algorithm is essentially based on a new large neighborhood structure. Indeed, in LS heuristics, designing operators to explore large promising regions of the search space may improve the quality of the obtained solutions. However, designing such neighborhood is at the expense of a highly computationally process. Therefore, the use of graphics processing units (GPUs) provides an efficient complementary way to speed up the search. The proposed GPU-based iterated tabu search has been experimented on 5 different Q3AP instances. The obtained results are convincing both in terms of efficiency, quality and robustness of the provided solutions at run time.Index Terms-Quadratic 3-dimensional assignment problem (Q3AP), GPU-based local search, metaheuristics on GPU, iterated tabu search on graphics processing units.

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“…Their implementation for a Grid environment features the synchronous multi-start, parallel evaluation of different solutions and asynchronous migration. Loukil et al implemented a two-level parallel GA (genetic algorithm) to solve the quadratic 3-dimensional assignment problem (Q3AP) [21]. In the first level, a number of GA's evolve in parallel and in the second level, individuals are transformed in parallel in each GA.…”

Section: Multiple Markov Chain Psamentioning

confidence: 99%

Load balancing on temporally heterogeneous cluster of workstations for parallel simulated annealing

Moharil

Lee

2010

Cluster Comput

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Simulated annealing (SA) is a general-purpose optimization technique widely used in various combinatorial optimization problems. However, the main drawback of this technique is a long computation time required to obtain a good quality of solution. Clusters have emerged as a feasible and popular platform for parallel computing in many applications. Computing nodes on many of the clusters available today are temporally heterogeneous. In this study, multiple Markov chain (MMC) parallel simulated an-nealing (PSA) algorithms have been implemented on a temporally heterogeneous cluster of workstations to solve the graph partitioning problem and their performance has been analyzed in detail. Temporal heterogeneity of a cluster of workstations is harnessed by employing static and dynamic load balancing techniques to further improve efficiency and scalability of the MMC PSA algorithms.

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A parallel hybrid genetic algorithm-simulated annealing for solving Q3AP on computational grid

Cited by 13 publications

References 23 publications

Interval-based initialization method for permutation-based problems

Interval-based initialization method for permutation-based problems

A GPU-based iterated tabu search for solving the quadratic 3-dimensional assignment problem

Load balancing on temporally heterogeneous cluster of workstations for parallel simulated annealing

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