In this dissertation, an optimal algorithm-based fuzzy behavior decision system is proposed for a small-sized chip automatic programming equipment to improve the production capacity of equipment. Two main designed topics of equipment simulator and behavior decision system are studied. In the equipment simulator design, a simulator is designed and implemented for the small-sized chip automatic programming equipment to simulate its production capacity. Moreover, depending on different programming time, the change of production capacity is studied for different platform configuration and different number of programmers. In the behavior decision system design, an optimal algorithm-based fuzzy behavior decision system is proposed to improve the production capacity. First of all, based on characteristics of the small-sized chip automatic programming equipment, a two-inputs-and-one-output fuzzy system structure is constructed. It allows the equipment to determine a next appropriate action based on the current status of each programmer. Then two optimal algorithms of GA and PSO are applied to automatically select a better parameter set so that the corresponding fuzzy behavior decision system can let the equipment have a better production capacity. Finally from the simulation results, we can see that the implemented simulator can indeed provide a method to decide an appropriate platform configuration and an appropriate number of programmers for different programming time. And the proposed method can indeed improve the production capacity and reduce the impact in some abnormal conditions.