Comparer des méthodes

	Ordonnancement d'ateliers	Équilibrage de chaîne de montage
Domaine	Gestion des opérations	Gestion des opérations
Famille	Machine learning	Machine learning
Année d'origine	2016	2010
Auteur d'origine	Pinedo, M. L.	Scholl, A.
Type	Combinatorial scheduling problem	Optimization problem
Source fondatrice	Pinedo, M. L. (2016). Scheduling: Theory, algorithms, and systems (5th ed.). Cham: Springer.	Scholl, A. (2010). Balancing and sequencing of assembly lines. Physica-Verlag.
Alias	job scheduling, machine scheduling	line balancing, workload balancing
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.	Assembly Line Balancing is the problem of distributing a sequence of assembly tasks across a series of workstations on a production line such that work is evenly distributed, idle time is minimized, and throughput constraints are satisfied. The goal is to assign tasks to stations such that the total work time at each station is as equal as possible, optimizing for production rate (cycle time) and resource utilization. This is a classic optimization problem in manufacturing, solved through heuristic and exact algorithms, essential to the efficiency of mass production systems.