This paper treats a two-echelon inventory system. The higher echelon is a single location reffered to as the depot, which places orders for supply of a single com modity. The lower echelon consists of several points, called the retailers, which are supplied by shipments from the depot, and at which random demands for the item occur. Stocks are reviewed and decisions are made periodically. Orders and/or shipments may each require a fixed lead time before reaching their respective desti nations. Section II gives a short literature review of distribution research. Section III introduces the multi-echelon distribution system together with the underlying as sumptions and gives a description of how this problem can be viewed as a Markovian Decision Process. Section IV discusses the concept of cost modifications in a distribution context. Section V presents the test-examples together with their optimal solutions and also gives the characteristic properties of these optimal solutions. These properties then will be used in section VI to give adapted ver sions of various heuristics which were used in assembly experiments previously and which will be tested against the test-examples.

Some Modelling Theoretic Remarks on Multi-Stage Production Planning

Inventory - Production and Distribution Systems
Two-Stage Production Planning in a Dynamic Environment
Overview of a Stock Allocation Model for a Two-Echelon Push System Having Identical Units at the Lower Echelon
System - Based Heuristics for Multi-Echelon Distribution Systems
A Branch and Bound Algorithm for the Multi Item Single Level Capacitated Dynamic Lotsizing Problem
Multi-Stage Lot-Sizing
Aggregating Items in Multi-Level Lot Sizing
Optimal Lot-Sizing for Dynamic Assembly Systems
Planning Component Delivery Intervals in Constrained Assembly Systems
Multi-Stage Lot-Sizing for General Production Systems
Practical Applications and Hierarchical Integration Problems
Practical Application of the Echelon Approach in a System with Divergent Product Structures
Hierarchical Production Planning: Tuning Aggregate Planning with Sequencing and Scheduling
The Design of an Hierarchical Model for Production Planning and Scheduling
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