Generative communication in Linda
ACM Transactions on Programming Languages and Systems (TOPLAS)
Coordination languages and their significance
Communications of the ACM
The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
A taxonomy and survey of grid resource management systems for distributed computing
Software—Practice & Experience
A Taxonomy of Hybrid Metaheuristics
Journal of Heuristics
The Distributed Genetic Algorithm Revisited
Proceedings of the 6th International Conference on Genetic Algorithms
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
Multicriteria Scheduling: Theory, Models and Algorithms
Multicriteria Scheduling: Theory, Models and Algorithms
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
Parallel Approaches for Multiobjective Optimization
Multiobjective Optimization
The asynchronous island model and NSGA-II: study of a new migration operator and its performance
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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In this paper, we contribute with the first results on parallel cooperative multi-objective meta-heuristics on computational grids. We particularly focus on the island model and the multi-start model and their cooperation. We propose a checkpointing-based approach to deal with the fault tolerance issue of the island model. Nowadays, existing Dispatcher-Worker grid middlewares are inadequate for the deployment of parallel cooperative applications. Indeed, these need to be extended with a software layer to support the cooperation. Therefore, we propose a Linda-like cooperation model and its implementation on top of Xtrem Web. This middleware is then used to develop a parallel meta-heuristic applied to a bi-objective Flow-Shop problem using the two models. The work has been experimented on a multidomain education network of 321 heterogeneous Linux PCs. The preliminary results, obtained after more than 10 days, demonstrate that the use of grid computing allows to fully exploit effectively different parallel models and their combination for solving large-size problem instances. An improvement of the effectiveness by over 60% is realized compared to serial meta-heuristic.