Optimal pump scheduling has been applying to decrease operating costs of water distribution systems (WDSs). However, the operations of pumping stations will result in an increase of Greenhouse gas emission (GHG). To reduce GHG, pumping stations should be operated with high efficiency. For this reason, optimal pump cheduling should take into account both energy cost savings and pumping station efficiency. The aim of this article is to suggest an efficient multi-objective optimization solution or minimizing pumping energy cost and maximizing pumping station efficiency. As a result, a trade-off solution compromising pumping energy cost and pumping system efficiency will be achieved. The Genetic Algorithm (GA) combined with a WDS simulator, EPANET will be applied to solve the pump scheduling problem in one benchmark WDS and the results from our solution will be compared to the ones in the literature in terms of pumping energy cost and efficiency.