This paper presents a distributed software architecture that allows the cooperation among research institutions in the field of Combinatorial Optimization-DEVOpT: Distributed Evolutionary Optimization Centers. It has as main aims to share existing algorithms for optimization problems, to allow the easy testing of these algorithms with existing instances, to provide fast and better ways to design new algorithms, and to share computational power among the cooperating institutions. This is achieved respecting the autonomy and heterogeneity of the cooperating institutions. The distributed architecture is discussed here and also a case study of a Paxailel Memetic Algorithm to solve the Asymmetric Traveling Salesman Problem (ATSP) running on this environment is analyzed.
This paper presents a distributed software architecture that allows the cooperation among research institutions in the field of Operations Research. It has as main aims to share existing algorithms for optimization problems, to allow the easy testing of these algorithms with existing instances, and to share computational power among the cooperating institutions. This is achieved respecting the autonomy and heterogeneity of the cooperating institutions. The five functional blocks that build the architecture are discussed here and also a study case of a Parallel Memetic Algorithm to solve the Traveling Salesman Problem running on this environment is analysed.
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