Stochastic Models For Make To Stock Production Inventory Systems

Stochastic Models for Make-to-stock Production-inventory Systems

This thesis considers a class of single-stage, single-product Make-to-Stock Production/Inventory Systems (MTS systems) with backorders, under various replenishment policies. It studies two types of stochastic models for such MTS systems: a discrete model and a stochastic fluid model (SFM). In a discrete model of an MTS system, order fulfillment from inventory following demand arrivals and inventory restocking following replenishment arrivals are modeled as discrete jumps in the inventory position level. In contrast, stocks in an SFM are treated as fluid, and demand fulfillment and inventory replenishment are carried out continuously, as stock flows into and out of inventory driven by flow rates. We then proceed to derive formulas for Infinitesimal Perturbation Analysis (IPA) derivatives in such MTS systems, and show them to be unbiased under appropriate conditions.

Stochastic Models of Production-inventory Systems

Handbook of Stochastic Models and Analysis of Manufacturing System Operations

This handbook surveys important stochastic problems and models in manufacturing system operations and their stochastic analysis. Using analytical models to design and control manufacturing systems and their operations entail critical stochastic performance analysis as well as integrated optimization models of these systems. Topics deal with the areas of facilities planning, transportation, and material handling systems, logistics and supply chain management, and integrated productivity and quality models covering: • Stochastic modeling and analysis of manufacturing systems • Design, analysis, and optimization of manufacturing systems • Facilities planning, transportation, and material handling systems analysis • Production planning, scheduling systems, management, and control • Analytical approaches to logistics and supply chain management • Integrated productivity and quality models, and their analysis • Literature surveys of issues relevant in manufacturing systems • Case studies of manufacturing system operations and analysis Today’s manufacturing system operations are becoming increasingly complex. Advanced knowledge of best practices for treating these problems is not always well known. The purpose of the book is to create a foundation for the development of stochastic models and their analysis in manufacturing system operations. Given the handbook nature of the volume, introducing basic principles, concepts, and algorithms for treating these problems and their solutions is the main intent of this handbook. Readers unfamiliar with these research areas will be able to find a research foundation for studying these problems and systems.