Multiprocessor scheduling belongs to a special category ofNP-complete computational problems. The purpose of scheduling is to scatter tasks among the processors in such a way that the precedence. constraints behveen tasks are kept, and the total execution time is minimized. Cellular automata (CA) can be used for multiprocessor scheduling, but one of Site difficulties in using CA is the exponentially increasing number of rules with increasing number of processor and neighborhood radhis. Here.. we propose a combined use of ant colony and evolutionary meta- lieuristics to search the rule\\\'s feasible space in order to find optimal rule base. Also we introduce a fti-\\\'o dimensional cellular automata structure based on the important task attributes in the precedence task. graph. The proposed scheduler that uses evolving cellular automata based on ant colony can find optimal response time for some of well known precedence task graph in the multiprocessor scheduling area.

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