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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.
This book presents a comprehensive overview of recent developments in production planning. The monograph begins with an introductory chapter reviewing the need for these production planning models, that operate by determining time-phased releases of work into the facility or supply chain, relating these to the Manufacturing Planning and Control (MPC) and Advanced Planning and Scheduling (APS) frameworks, that form the basis of most academic research and industrial practice. The extensive body of work on Workload Control is also placed in this context, and proves the need for improved models with a discussion of the difficulties, these approaches encounter. The next two chapters present a detailed review of the state of the art in optimization models based on exogenous planned lead times, and examines the cases where these can take both integer and fractional values. The difficulties arising in estimating planned lead times are consistent with factory behavior which are highlighted, noting that many of these lead to non-convex optimization models. Attempts to address these difficulties by iterative multimodel approaches, that combine simulation and mathematical programming, are also discussed in detail. The next three chapters of the volume address the set of techniques developed using clearing functions, which represent the expected output of a resource in a planning period, as a function of the expected workload of the resource, during that period. The chapters on this subject propose a basic optimization model for multiple products, discuss the difficulties of this model and some possible solutions. It also reviews prior work, and discuss a number of alternative formulations of the clearing function concept with their respective advantages and disadvantages. Applications to lot sizing decisions and a number of other specific problems are also described. This volume concludes with an assessment of the state of the art described in the volume, and several directions for future work.
​This book extends the existing demand fulfillment research by considering multi-stage customer hierarchies. Basis is a two-step allocation and consumption planning procedure. In the existing literature, it is assumed that the customer segments are ‘flat’. This means they can be sorted easily during the allocation planning step by a single central planner in decreasing order of profitability. In the subsequent consumption planning phase, if order requests differ in terms of profit margins, companies can render prioritized service in real time to their most profitable customers by consuming the reserved quotas.
Manufacturers worldwide are faced with unprecedented challenges from international competition, changing production processes and technologies, shorter production life-cycles, market globalization and environmental requirements. Fundamental to meeting these challenges is the understanding and control of information across all stages of the Computer Integrated Manufacturing (CIM) process. Modern Manufacturing presents the state of the art in the information-oriented aspects of CIM and Intelligent Manufacturing Systems. Particular emphasis is placed on the impact of new software engineering technologies, the object-oriented approach, database design, hierarchical control and intelligent systems. The contributions are written by experts from Europe and the USA.
The book presents the results of the joint annual conference of the four Operations Research Societies DGOR, GM\OR, \GOR and SVOR, held in Vienna in 1990. The main goal was to present practical experiences as well as theoretical results. Both aspects are covered in a balanced way. Papers cover topics from the fields Optimization, Stochastic Modells, Decision Theory and Multicriteria Decision Making, Control Theory, Mathematical Economics, Game Theory, Macroeconomics, Econometrics and Statistics, Supercomputing and Simulation, Non-linear Systems, Artificial Intelligence and Expert Systems, Fuzzy Sets and Systems, Production, Logistics, Inventory and Marketing among others.