Papers

@article{Cancela2005444,

title = {Two-phase multiobjective optimization},

author = {Alberto Cancela and Julián Dorado and Juan R. Rabuñal-Dopico and Alejandro Pazos},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-21944444152&partnerID=40&md5=0096ceaadbbd0674df83823911c71761},

issn = {17900832},

year  = {2005},

date = {2005-01-01},

urldate = {2005-01-01},

journal = {WSEAS Transactions on Information Science and Applications},

volume = {2},

number = {5},

pages = {444-449},

abstract = {This work proposes a genetic algorithm (GA) based approach for the search of the Pareto optimal set of a multiobjective optimization problem. First the global population is divided into various subpopulations. The algorithm operation consists of two phases: firstly each subpopulation tries to optimize a different objective; later the algorithm searches for good compromise solutions between objectives. Information is exchanged by means of the migration of individuals during the second phase. A weighted sum is used for fitness calculation. Weight vectors are randomly generated for each selection event, which creates a wide range of search directions. The good behaviour of the proposed algorithm becomes visible in its application to some continuous problems.},

note = {cited By 1},

keywords = {Evolutionary algorithms; Genetic algorithms; Pareto principle; Vectors, Metapopulation evolutionary algorithm; Multiobjective optimization; Pareto optimal set, Optimization},

pubstate = {published},

tppubtype = {article}

}