<p>The simultaneous planning of project scheduling and material ordering has been extensively investigated to achieve flexible project execution. However, this problem is rarely examined under storage space constraints. In this paper, a mixed-integer nonlinear programming model is developed that considers activity precedence relationships, material supply time restrictions, and storage space constraints, with the goal of minimizing total project costs. Subsequently, two types of heuristic algorithms—the priority-based algorithm and the genetic algorithm—are designed to solve the proposed model. Computational experiments are conducted using the publicly accessible PSPLIB dataset to validate the effectiveness of these algorithms. Furthermore, a sensitivity analysis of project characteristics and cost parameters is performed to reveal their effects on the performance of both algorithms.</p>