The Sequential Multi-Objective Genetic Algorithm: A novel multi-objective genetic algorithm

In this paper, a new multi-objective evolutionary algorithm is proposed. This new algorithm called the Sequential Multi-Objective Genetic Algorithm (SEQ-MOGA), overcomes some weaknesses that are observed in the Non-Dominated Sorting Genetic Algorithm II (NSGAII). This superior performance of the SEQ-MOGA is obtained via introducing a novel technique for the survivor selection of the algorithm. In fact, the proposed SEQ-MOGA intends to arrange the individuals in an orderly sequence so that the individuals are uniformly spread throughout the entire Pareto front. In order to evaluate the performance of the SEQ-MOGA, this algorithm is compared with some famous MOEAs (Multi-Objective Evolutionary Algorithms). In this regard, two performance metrics are used to measure the effectiveness of the proposed SEQ-MOGA. The experimental results clearly support the superiority of the proposed algorithm against those well-known algorithms