A simulation-optimization approach to parameterize Demand-Driven Material Requirements Planning. Issue 10 (2022) - Damand, David; Lahrichi, Youssef; Barth, Marc
Abstract: Since its inception ten years ago, many researchers have shown Demand-Driven Material Requirements Planning (DDMRP) to be an efficient production planning method in terms of customer satisfaction and operating costs. DDMRP introduces a novel Net Flow Equation (NFE) to decide when to launch an order and how much to order. DDMRP relies on many parameters that affect the NFE and therefore the supply orders. The present paper investigates how to fix these parameters. We formulate this problem as a multi-objective optimization problem. The minimization of the average on-hand inventory is considered simultaneously with the maximization of customers' orders delivered on-time (OTD: On-Time Delivery). To solve the formulated optimization problem, a multi-objective metaheuristic (NSGA-II: Non-dominated Sorting Genetic Algorithm) is coupled with a simulation algorithm. The front of non-dominated solutions is analysed for a given randomly-generated data instance. Other experiments are to be held on data provided by a private company.