The uncoordinated charging strategy of massive electric vehicles (EVs) will threaten the safe operation of the grid, this situation can be relieved if coordinated charging/discharging strategy is developed. Based on classical battery-wear model and time-of-use price, a multi-objective optimal model for EVs’ charging/discharging process is proposed to reduce the daily load fluctuation and the charging cost considering EV’s charging demand. The Pareto front and the compromise solution are calculated by equilibrium-inspired multiple group search optimization with synergistic learning (EMGSS). Rolling optimization is adapted to deal with the day and night random variance of charging demand and reach the double-win of grid and EV owners. The simulation results demonstrate that daily load fluctuation is reduced effectively and EVs’ charging cost is also decreased.