Convexity plays an imperative role in optimization, pattern classication and recognition, image processing and many other relating topics in dierent elds of mathematical sciences like operation research, numerical analysis etc. The concept of soft sets was rst formulated by Molodtsov as a completely new mathematical tool for solving problems dealing with uncertainties. Smarandache conceptualized hypersoft set as a generalization of soft set (hS;E) as it transforms the function hS into a multi-attribute function hHS. Deli introduced the concept of convexity cum concavity on soft sets to cover above topics under uncertain scenario. In this study, a theoretic and analytical approach is employed to develop a conceptual framework of convexity cum concavity on hypersoft set which is generalized and more eective concept to deal with optimization relating problems. Moreover, some generalized properties like -inclusion, intersection and union, are established. The novelty of this work is maintained with the help of illustrative examples and pictorial version rst time in literature.
No takes yet. Share an insight, caveat, or question.
Rahman et al. (2020) studied this question.
Synapse has enriched 5 related papers. Consider them for comparative context: