The ever-increasing requirement for reliability and quality of supply suggests to enable the self-healing features of modern distribution networks employing the intelligent measurement, communication, and control facilities of smart grids. In this paper, the concept of multiagent automation in smart grids is applied to build a self-healing framework to be used for restoration service. In this regard, an agent interaction mechanism is designed to build a reduced model of only those parts of the network that could participate in the restoration process. This reduced model is subject to a global optimization method, aiming at restoring a maximum of loads with minimum switching operations. This optimization problem, including power flow constraints is formulated as a convex second-order cone programming and solved using GUROBI solver. The proposed multi-agent systems-based strategy is completely scalable and leads to a global optimum solution (up to the desired accuracy) in a short time, without the need for powerful processors. The simulation studies are carried out on a 70-bus distribution network in case of multiple fault scenarios, using MATLAB/Yalmip toolbox.