Economical power dispatch problem (EPDP) is urgent operation problem for system operators. The EPDP is formulated as multi-objective problem that simultaneously optimize two objectives namely generation fuel costs and emissions. EPDP is considered as a complex and non-convex problem. Because of its complexity in constraints and conflict nature, a multi-objective fruit-fly optimization algorithm (MO-FOA) is proposed to improve the economic issue with acceptable levels of emissions. This algorithm is initialized randomly with a swarm of fruit flies. During this initialization, the objective functions are simulated into single objective function. The application to the standard 30-bus IEEE system and ten unit generating system demonstrates the efficiency and robustness of the proposed MO-FOA to obtain well-scattered Pareto optimal solutions for the multi-objective EPDP. It is proven the promising characteristics of the proposed MO-FOA to solve highly complex problems in the single and multiobjective functions.