No abstract

Transgenetic algorithms are evolutionary computing techniques based on living processes where cooperation is the main evolutionary strategy. Those processes contain the movement of genetic material between living beings and endosymbiotic interactions. With the objective of having a better approximation between the proposed metaphor and the reality the algorithm also considers intracellular mechanisms of genetic information transposition and the quorum sensing, that is, the bacteria's ability for communicating and coordinating actions. To illustrate the application of a transgenetic algorithm to a difficult combinatorial optimization problem, an example is provided for the Traveling Purchaser Problem. The introduced approach is compared with two recent heuristics proposed for the same problem. The results of a computational experiment are reported and 9 new best solutions for benchmark instances are presented.

ResumoO presente trabalho apresenta um Algoritmo Transgenético para a solução do Problema do Caixeiro Comprador Capacitado Simétrico. O algoritmo é baseado em endossimbiose e outras transformações do fluxo intracelular. O algoritmo é descrito e experimentos computacionais são relatados no sentido de validar a eficiência da abordagem. São também apresentadas novas melhores soluções para 17 instâncias de um conhecido banco de instâncias para o problema.Palavras-chave: problema do caixeiro comprador capacitado simétrico; algoritmos evolucionários; algoritmos transgenéticos. AbstractThis paper presents a Transgenetic Algorithm to solve the Symmetric Capacitated Traveling Purchaser Problem. The biological inspiration of the proposed algorithm comes from the endosymbiotic theory of evolution. The algorithm is described and the results of computational experiments are reported. The performance of the algorithm is compared with other recent work presented in the literature. New best solutions for 17 instances of a known benchmark are reported.