Comparer des méthodes

	Ordonnancement d'ateliers	Planification des Besoins en Matières
Domaine	Gestion des opérations	Gestion des opérations
Famille	Machine learning	Machine learning
Année d'origine	2016	1975
Auteur d'origine	Pinedo, M. L.	Joseph Orlicky
Type	Combinatorial scheduling problem	Material planning algorithm
Source fondatrice	Pinedo, M. L. (2016). Scheduling: Theory, algorithms, and systems (5th ed.). Cham: Springer.	Orlicky, J. (1975). Material requirements planning: The new way of life in production and inventory management. New York: McGraw-Hill.
Alias	job scheduling, machine scheduling	MRP, MRP I
Apparentées	5	5
Résumé	Job shop scheduling is the problem of assigning a set of jobs (tasks) to a set of machines (resources) over time, subject to precedence and capacity constraints, with the goal of optimizing performance metrics such as makespan (total completion time), lateness, or cost. The job shop problem is a classic combinatorial optimization problem in operations research, addressed through heuristics (greedy dispatching rules, simulated annealing, genetic algorithms) and exact algorithms (branch-and-bound, constraint programming). It is fundamental to manufacturing, project management, and computational scheduling.	Material Requirements Planning (MRP) is a computerized system developed by Joseph Orlicky in the 1970s that calculates material requirements based on master production schedules and bill-of-materials data. MRP determines what materials to buy, how much to order, and when to order them to meet production demand while minimizing inventory carrying costs. It became a foundational technology for manufacturing planning and later evolved into manufacturing resource planning (MRP II) and enterprise resource planning (ERP) systems.