Effective replenishment planning and inventory control are essential for the smooth operation and adaptability of supply chains. These aspects play a pivotal role in upholding a company’s competitiveness and triumph in today’s fiercely competitive markets. Supply chain planners encounter significant hurdles in choosing the most appropriate suppliers in diverse scenarios, reducing average inventory levels, and determining optimal safety lead times. This research tackles these challenges by examining and evaluating a multi-period replenishment planning issue within the framework of dynamic demand and multiple suppliers. The suppliers are pre-selected and defined by procurement costs, with lead times considered as independent discrete random variables with known and limited probability distributions. The goal is to optimize the distribution of order quantities among these pre-selected suppliers while minimizing the anticipated total cost. Two strategies and corresponding linear models are suggested to investigate the impact of dividing orders between suppliers, order crossover, and order flexibility. Numerical experiments provide evidence that concurrently considering splitting and flexibility yields benefits in terms of cost optimization.