Lina GuenaneMokhtar HafayedShahlar MeherremSyed Abbas2025-10-06202001704214, 109914760170-42141099-147610.1002/mma.6392https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083397243&doi=10.1002%2Fmma.6392&partnerID=40&md5=62b8db435a65abe442725aca7adc707chttps://gcris.yasar.edu.tr/handle/123456789/9180In this paper we establish general necessary optimality conditions for stochastic continuous-singular control of McKean-Vlasov type equations. The coefficients of the state equation depend on the state of the solution process as well as of its probability law and the control variable. The coefficients of the system are nonlinear and depend explicitly on the absolutely continuous component of the control. The control domain under consideration is not assumed to be convex. The proof of our main result is based on the first- and second-order derivatives with respect to measure in Wasserstein space of probability measures and by using variational method. © 2020 Elsevier B.V. All rights reserved.EnglishMaximum Principle, Optimal Stochastic Continuous-singular Control, Second-order Derivative With Respect To Measure, Stochastic Differential Equation Of Mckean-vlasov Type, Equations Of State, Stochastic Control Systems, Stochastic Systems, Necessary Optimality Condition, Optimal Solutions, Probability Measures, Second Order Derivatives, Singular Control, Singular Stochastic Control, Variational Methods, Wasserstein Spaces, Vlasov EquationEquations of state, Stochastic control systems, Stochastic systems, Necessary optimality condition, Optimal solutions, Probability measures, Second order derivatives, Singular control, Singular stochastic control, Variational methods, Wasserstein spaces, Vlasov equationArticle