In a two-market genetic algorithm applied to a constrained optimization problem, two ‘markets’ are maintained. One market establishes fitness in terms of the objective functio...
Steven Orla Kimbrough, Ming Lu, David Harlan Wood,...
Abstract. A two-population Genetic Algorithm for constrained optimization is exercised and analyzed. One population consists of feasible candidate solutions evolving toward optimal...
We show how a random mutation hill climber that does multilevel selection utilizes transposition to escape local optima on the discrete Hierarchical-If-And-Only-If (HIFF) problem....
Abstract. A model of coevolutioinary genetic algorithms (COGA) consisting of two populations coevolving on two-bit landscapes is investigated in terms of the effects of random par...
Ming Chang, Kazuhiro Ohkura, Kanji Ueda, Masaharu ...
In this paper, we discuss the adaptability of Coevolutionary Genetic Algorithms on dynamic environments. Our CGA consists of two populations: solution-level one and schema-level o...