Comparer des méthodes

	Ordonnancement d'ateliers	Modèle SCOR
Domaine	Gestion des opérations	Gestion des opérations
Famille	Machine learning	Machine learning
Année d'origine	2016	1996
Auteur d'origine	Pinedo, M. L.	Pittiglio, Rabin, Todd & McGrath
Type	Combinatorial scheduling problem	Supply chain reference framework
Source fondatrice	Pinedo, M. L. (2016). Scheduling: Theory, algorithms, and systems (5th ed.). Cham: Springer.	Stewart, G. (1997). Supply chain operations reference model: SCOR, logistics information management, Vol. 10 No. 5, pp. 62-74.
Alias	job scheduling, machine scheduling	—
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.	The Supply Chain Operations Reference Model is a standardized framework for supply chain management developed by the Supply Chain Council (now APICS) in 1996. SCOR provides a structured approach to identify, evaluate, and improve supply chain processes across organizations, regardless of industry. It integrates planning, sourcing, manufacturing, delivery, and returns into a coherent operational model.