Abstract
Combing a genetic algorithm (GA) with a local search method produces a type of evolutionary algorithm (EA) known as a memetic algorithm (MA). This chapter presents a new memetic algorithm called OMA-MA (object migration automaton-based memetic algorithm) that behaves according to learning the automata-based memetic algorithm (LA-MA) model. Like LA-MA, OMA-MA has composed of two parts: a genetic section and a memetic section. Evolution is performed in the genetic section, and a local search is performed in the memetic section. The genetic section consists of a population of chromosomes, mutation operator, crossover operator, and a chromosome’s fitness function. The memetic section consists of a meme that corresponds to a local search method. The meme saves the effect (history) of its corresponding local search method. The meme is represented by an object migration automaton (OMA) whose states keep information about the local search process's history. Based on the relationship between the genetic section and the memetic section, three versions of OMA–MA called LOMA–MA, BOMA-MA, and HOMA–MA are presented.
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