Purpose In the competitive e-commerce environment, self-operated firms independently manage procurement, logistics and sales, yet often experience inefficiencies due to weak coordination, forecast errors and supply chain disruptions. This study investigates the multi-period, multi-product inventory routing problem with procurement decisions under quantity discounts (MMIRP-QD), aiming to jointly optimize procurement, transportation and warehousing decisions to improve replenishment efficiency, operational profitability and customer satisfaction. Design/methodology/approach An integrated optimization framework is developed for the MMIRP-QD, which incorporates quantity discounts, replenishment lead times, stockout penalties and a flexible replenishment strategy. First, an innovative demand forecasting model is proposed to enhance prediction accuracy. Second, a hybrid two-level heuristic with a crossover-repair operator improves computational efficiency. Third, a rolling-horizon approach is developed to handle forecast errors and dynamic disruptions. The proposed framework is illustrated through a case study. Findings Computational experiments demonstrate that the proposed approach outperforms benchmark methods in solution quality and efficiency. Furthermore, the rolling-horizon approach effectively mitigates forecast-error propagation. Sensitivity analysis further explores the effects of replenishment strategy and stockout penalties, yielding actionable managerial insights. Originality/value This study extends the standard MIRP by incorporating procurement decisions under quantity discounts, thereby formulating the MMIRP-QD, and proposes an integrated framework that combines demand forecasting, hybrid heuristic optimization and a rolling-horizon approach. By linking prediction with optimization, the framework provides a robust and scalable decision support tool for self-operated e-commerce decision making.