Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Using AspectJ to separate concerns in parallel scientific Java code
Proceedings of the 3rd international conference on Aspect-oriented software development
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Implementing Metaheuristic Optimization Algorithms with JECoLi
ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
Computer Methods and Programs in Biomedicine
Incrementally developing parallel applications with AspectJ
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Parallelism and evolutionary algorithms
IEEE Transactions on Evolutionary Computation
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A large number of optimization problems within the field of Bioinformatics require methods able to handle its inherent complexity (e.g. NP-hard problems) and also demand increased computational efforts. In this context, the use of parallel architectures is a necessity. In this work, we propose ParJECoLi, a Java based library that offers a large set of metaheuristic methods (such as Evolutionary Algorithms) and also addresses the issue of its efficient execution on a wide range of parallel architectures. The proposed approach focuses on the easiness of use, making the adaptation to distinct parallel environments (multicore, cluster, grid) transparent to the user. Indeed, this work shows how the development of the optimization library can proceed independently of its adaptation for several architectures, making use of Aspect-Oriented Programming. The pluggable nature of parallelism related modules allows the user to easily configure its environment, adding parallelism modules to the base source code when needed. The performance of the platform is validated with two case studies within biological model optimization.