A Multi-Objective de Novo Programming Models: a Review

• Autores: Iftikhar Ali Hussein, Hegazy Zaher, Naglaa Ragaa Saeid, Heba Sayed Roshdy
• Localización: International Journal of Professional Business Review: Int. J. Prof.Bus. Rev., ISSN 2525-3654, ISSN-e 2525-3654, Vol. 9, Nº. 1, 2024 (Ejemplar dedicado a: Continuous publication; e04284)
• Idioma: inglés
• DOI: 10.26668/businessreview/2023.v9i1.4180
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• Resumen

  • Purpose: In this article, the published articles of this type of programming (DNP) were reviewed and classified according to the conditions of its use into two types: 1) De Novo programming under certainty, 2) De Novo programming under uncertainty, and the second type has been classified into four types: 1) Interval de novo programming, 2) Fuzzy de novo programming, 3) Type-II Fuzzy de novo programming, 4) Stochastic de novo programming, in addition to that, the articles were classified according to the author’s, years of publication, type of (DNP) model, solution approach, validation and field of application.

      Theoretical Framework: Most of the methods used in operations research focus on maximizing or optimizing existing available systems, but there are other suggested methods and methodologies that have been applied to design new systems such as De Novo programming, so there is a difference between improving an available system and designing an improved system.

      Design/Methodology/Approach: We analyzed the De novo programming from 2017 to 2023. We identified when, who, where and what was published on the subject.

      Findings: The results of this study resulted in a number of conclusions, including: that all the proposed models in the improvement of the De Novo programming model seek to design an optimum system by removing trade-offs between goals and redesigning the model. Through the articles reviewed and especially the uncertainty in the model, the researchers used fuzzy programming the most in addressing the uncertainty of FDNP: reaching 31%, either SDNP: 5%, FIDNP: 3% and IDNP: 3%.

      Research, Practical & Social Implications: We suggest a future research agenda and highlight to the methods that used to solve DNP under certainty and uncertainty.

      Originality/Value: The results indicate that the number of publications is growing, and the application of de Novo programming in the fields of (agriculture, industry and irrigation) more than the rest of the fields.