A new polynomial-time algorithm for linear programming
Combinatorica
Customer-order information, leadtimes, and inventories
Management Science
Mathematical programming models of discrete event system dynamics
Proceedings of the 32nd conference on Winter simulation
Feature Article: Optimization for simulation: Theory vs. Practice
INFORMS Journal on Computing
Integrating Replenishment Decisions with Advance Demand Information
Management Science
Proceedings of the 35th conference on Winter simulation: driving innovation
Inventory Control with Limited Capacity and Advance Demand Information
Operations Research
Kanban policy improvement thanks to a (max,+)-algebra analysis
International Journal of Systems Science - Production Coordination and Inventory Policies
Token-based pull production control systems: an introductory overview
Journal of Intelligent Manufacturing
An integrated framework for card-based production control systems
Journal of Intelligent Manufacturing
A time-based decomposition algorithm for fast simulation with mathematical programming models
Proceedings of the Winter Simulation Conference
Hi-index | 0.00 |
Pull policies may perform quite differently depending on the particular manufacturing system they must control. Hence, it is clear the necessity of having efficient performance evaluation models to select the best control policy in a specific context. This paper proposes a mathematical programming representation of the main pull control policies applied to single-product serial manufacturing systems. The proposed models simulate the pull controlled system in the sense that, if instantiated with the same parameter values as in a simulation model, their solution gives the same event sequence of the simulation. The proposed mathematical representation is also used for a formal comparison of the considered pull control policies. The new models presented in this paper can represent a base to build new efficient optimization algorithms for the design of pull controlled production systems.