Kanazaki, M., & Toyoda, T. (2025). Enhancing constrained MOEA/D with direct mating using hybrid mating strategies and diverse crossover methods. Neural Computing and Applications, 37(33), 27729-27746. https://doi.org/10.1007/s00521-024-10908-6
ISO-690 (author-date, English)KANAZAKI, Masahiro and TOYODA, Takeharu, 2025. Enhancing constrained MOEA/D with direct mating using hybrid mating strategies and diverse crossover methods. Neural Computing and Applications. 1 November 2025. Vol. 37, no. 33, p. 27729-27746. DOI 10.1007/s00521-024-10908-6.
Modern Language Association 9th editionKanazaki, M., and T. Toyoda. “Enhancing Constrained MOEA/D With Direct Mating Using Hybrid Mating Strategies and Diverse Crossover Methods”. Neural Computing and Applications, vol. 37, no. 33, Nov. 2025, pp. 27729-46, https://doi.org/10.1007/s00521-024-10908-6.
Mohr Siebeck - Recht (Deutsch - Österreich)Kanazaki, Masahiro/Toyoda, Takeharu: Enhancing constrained MOEA/D with direct mating using hybrid mating strategies and diverse crossover methods, Neural Computing and Applications 2025, 27729-27746.
Emerald - HarvardKanazaki, M. and Toyoda, T. (2025), “Enhancing constrained MOEA/D with direct mating using hybrid mating strategies and diverse crossover methods”, Neural Computing and Applications, Vol. 37 No. 33, pp. 27729-27746.