In view of the flexible job shop scheduling problem,an improved multi-objective salp swarm algo-rithm combining decay factor and cross-variance operator is proposed.To facilitate the solution of the algorithm,a two-layer coding method of equal length is used and a conversion mechanism based on ascending order rules is intro-duced to achieve the conversion between individual position vectors and scheduling solutions.Chaotic mapping and a hybrid rule-based approach are used to generate a better initial population.A decay factor and a cross-variance operator are introduced in the position update of individuals to enhance the global search capability of the algorithm.The algorithm's solution performance is tested using standard and real-life examples of the scheduling problem and compared with other algorithms.The results show that the solution capability of the proposed improved multi-objec-tive salp swarm algorithm is significantly improved over the original algorithm,verifying the effectiveness of the im-proved algorithm in solving the flexible job shop scheduling problem.
维普
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