Abstract: To address the problem of equipment quantity configuration in an intelligent workshop with multi-resource collaboration, an optimization model is established with dual constraints on system output rate and production cycle and the objective of minimizing equipment purchase cost. Since the optimization problem is a stochastic nonlinear integer programming one, and the constraints cannot be expressed in closed form of decision variables, a simulation-based intelligent optimization algorithm is proposed to solve it. For such production workshops with multi-resource collaboration, a system performance evaluation model is developed based on a discrete event simulation platform. A gray wolf optimization algorithm embedded in the simulation model is proposed to obtain the optimization scheme of equipment quantity configuration. Through simulation experiments and optimization case comparisons, the superiority and stability of the proposed method over other algorithms in optimization results are verified. The optimal configuration scheme is determined by analyzing actual application cases, and the results verify the effectiveness of the proposed method, demonstrating its practical value.