Estimating clearing functions from simulation data

TL;DR: Two of the most widely used and considered best performing periodic order release models out of both streams are compared: the LUMS (rule based) and the clearing function model (optimisation based).

TL;DR: Two alternative approaches that have emerged in the recent literature are considered: the use of discrete-time linear programming models based on nonlinear clearing functions, and methods using systems of coupled partial differential equations based on transport phenomena.

TL;DR: The problem of planning future order releases in hierarchical production planning and control systems is considered, which represents the functional relationship between the level of WIP and the maximum output of a work centre in a period.

TL;DR: This work uses a simulation model of a scaled-down wafer fabrication facility to generate data and evaluates the performance of the resulting CFs, finding that using load based CFs yields better performance.

TL;DR: In this article, the authors present a Manufacturing Planning and Control (MPC) system for the Standard Normal Distribution (SND) distribution system, which is based on an Enterprise Resource Planning (ERP) model.

TL;DR: In this paper, the authors introduce a methodology for automated production planning of semiconductor manufacturing based on iterative linear programming (LP) optimization and discrete-event simulation calculations and demonstrate in experiments on an industry data set that a relatively small number of iterations is required to develop a production plan correctly characterizing future flow times as a function of factory load and product mix.

TL;DR: Optimization Modeling starts with an mrp Model and extends to an MRP II Model, a Better Model and Extensions to the Model, and Implementation Examples.

TL;DR: Holt and Simon as discussed by the authors proposed a linear decision rule for production and employment scheduling with a quadratic cost function involving inventory, overtime, and employment costs, and the numerical coeff...