In logistics systems, the issue of planning stability has attracted increased attention and interest in recent years. This is mainly due to an increasing integration of planning systems both within and across companies in supply chain management. The propagation of adjustments in planning systems first acquired wide attention when MRP systems were employed as standard planning tools for material coordination. Within a rolling horizon framework the MRP application produced considerable planning instability which origins from uncertainties in the planner's exogenous environment as well as from endogenous sources. This book presents an analytical investigation that gives deep insight into the influence of different kind of inventory control rules on the stability of material planning systems under stochastic demand in a rolling horizon environment.

Increasing customer needs, the globalization of markets and the evolution of e-commerce add to the complexity of logistic processes. In today's business, it is well understood that an effective management of logistic processes is impossible without the use of computer-based tools and quantitative methods. This book presents in a systematic way quantitative approaches to distribution logistics and supply chain management. The main orientation of the book is towards practical problem solving, and numerous case studies and practical applications are presented. The topics covered include: supply chain management, revers logistics, e-commerce, facility location and network planning, vehicle routing, warehousing, inventory control.

This book seeks to give better solutions to managers managing MRP systems in manufacturing organizations. It introduces the concept of multi-pass heuristics in MRP context and shows that in variety of conditions of the shop floor (such as high and low variations in machine utilisation) these (multi-pass given in this book) can be applied to give better performance on the criterion of total aggregate (or units) lateness with insignificant rise in total costs The author explains a heuristic that modifies the holding cost (of items/assemblies that have higher difference of actual and the theoretical holding costs) and empirically shows that this is better than the heuristic that modified the lead time (of items/assemblies that have higher difference of actual and the theoretical holding costs). The book also talks about a series of heuristics that seek to attain co-ordinated arrival of assemblies at assembly centers with encouraging results

Von der Produktidee über den Prototyp und die Modellsimulation bis zur Analyse: Dieser Band hilft Entwicklern und Designern beim Verständnis aller Abläufe im Zuge des Designs neuer Produkte, Prozesse und Systeme. Eine Fülle von Beispielen industrieller Anwendungen, realer Probleme und zugehöriger Lösungen hilft beim Vertiefen und Umsetzen des Stoffes. (05/00)

This textbook provides a practice-oriented introduction into Analytics-based inventory management in complex supply chains. In the context of Business Analytics, we concentrate on Prescriptive Analytics. In addition to standard single-level inventory models also multi-level approaches for the optimal allocation of safety inventory are presented. Moreover, dynamic lot sizing problems under random demand and random yield and their relationship to Material Requirements Planning (MRP) are discussed.The models and algorithms are illustrated with the help of numerous examples. The book has been written for students of Supply Chain Management and Operations Management as well as for practitioners who are confronted with inventory management in their daily work.

The scope of this book is limited to heuristics, metaheuristics, and approximate methods and algorithms as applied to planning and scheduling problems. While it is not possible to give a comprehensive treatment of this topic in one book, the aim of this work is to provide the reader with a diverse set of planning and scheduling problems and different heuristic approaches to solve them. The problems range from traditional single stage and parallel machine problems to more modern settings such as robotic cells and flexible job shop networks. Furthermore, some chapters deal with deterministic problems while some others treat stochastic versions of the problems. Unlike most of the literature that deals with planning and scheduling problems in the manufacturing and production environments, in this book the environments were extended to nontraditional applications such as spatial scheduling (optimizing space over time), runway scheduling, and surgical scheduling. The solution methods used in the different chapters of the book also spread from well-established heuristics and metaheuristics such as Genetic Algorithms and Ant Colony Optimization to more recent ones such as Meta-RaPS.