This paper examines the use of hybrid metaheuristic algorithms to optimize order quantity in a single manufacturer-multi-supplier two-level JIT supply chain in production system. Over the years, production systems have largely been controlled by either MRP (Material Requirements Planning), JIT (Just in Time) or OPT (Optimized Production Technology) paradigm. In the supply chain environment, traditional material demand planning does not consider the supplier's supply capacity and economic benefits, which is not conducive to the long-term cooperation of upstream and downstream enterprises in the supply chain. The main goal of this paper is to optimize ordering batches based on MRP and JIT in supply chain. There is limited research designing and optimizing the supply chain / procurement network. This study is among the first to integrate supplier selection to optimize performance indicators in supply chain network design considering minimization of total cost of JIT supply chain order batch coordination adjustment model. The BOM constraints and MRP formulation principles of product production are followed to minimize the supply chain the total cost of downstream companies’ inventory, transportation, out of stock, and crashing is the target. The MRP-led supply chain ordering batch collaborative optimization model is constructed; the manufacturer’s main production plan is adjusted to change the procurement plan to obtain supplier supplies according to the scheme, an improved discrete particle swarm optimization algorithm and genetic algorithm is designed to solve the model; the feasibility of the model is verified by an example. The effectiveness of the algorithm is proved through the analysis and comparison of the algorithm results.