Multiple cracking furnaces in an ethylene plant tun in parallel to produce ethylene, propylene, and other products from different hydrocarbon feedstocks. Because both coke formation in radiant coils and change of operation Conditions with time have significant effects on the performance of cracking furnaces, it is better for the cyclic scheduling to be simultaneously optimized with the operation conditions. To match this real requirement, a mixed-integer dynamic optimization (MIDO) problem is presented for the optimization of both operation conditions and cyclic scheduling simultaneously, through which the optimal assignment, the processing time, the subcycle number, and the optimal operation conditions of different feeds in different cracking furnaces are determined at the same time. To solve the MID problem, it is discretized and converted into a large scale mixed-integer nonlinear programming (MINLP) problem. The two scheduling cases of a cracking furnaces system are illustrated showing a remarkable increase in the economic performance as compared with that of the traditional Method.