Future Generation Computer Systems - Special issue: Bio-inspired solutions to parallel processing problems
Graph partitioning models for parallel computing
Parallel Computing - Special issue on graph partioning and parallel computing
Shape-optimized mesh partitioning and load balancing for parallel adaptive FEM
Parallel Computing - Special issue on graph partioning and parallel computing
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Migration Policies, Selection Pressure, and Parallel Evolutionary Algorithms
Journal of Heuristics
Aspect Radio for Mesh Partitioning
Euro-Par '98 Proceedings of the 4th International Euro-Par Conference on Parallel Processing
A hybrid graph-genetic method for domain decomposition
Finite Elements in Analysis and Design
Multilevel Mesh Partitioning for Optimizing Domain Shape
International Journal of High Performance Computing Applications
A resource-constrained assembly job shop scheduling problem with Lot Streaming technique
Computers and Industrial Engineering
Graph partitioning and disturbed diffusion
Parallel Computing
Ad-hoc cluster and workflow for parallel implementation of initial-stage evolutionary optimum design
Structural and Multidisciplinary Optimization
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In this paper, parallel mesh-partitioning algorithms are proposed for generating submeshes with optimal shape using evolutionary computing techniques. It is preferred to employ a formulation for mesh partitioning, which maintains constant number of design variables irrespective of the size of the mesh. Two distinct parallel computing models have been employed. The first model of parallel evolutionary algorithm uses the master-slave concept (single population model) and a new synchronous model is proposed to optimise the performance even on heterogeneous parallel hardware. Alternatively, a multiple population model is also developed which simulates it's sequential counter part. The advantage of the second model is that it can fit in large size problems with large population even on moderate capacity parallel computing nodes. The performance of the evolutionary computing based mesh-partitioning algorithm is demonstrated first by solving several practical engineering problems and also several benchmark test problems available in the literature and comparing the results with the multilevel algorithms. Later the speedup of the parallel evolutionary algorithms on parallel hardware is evaluated by solving large scale practical engineering problems.