Model-Based Control of Logistics Processes in Volatile Environments - Decision Support for Operations Planning in Supply Consortia (Hardcover, 2011 ed.)


This monograph presents results originating from a research project investigating autonomous adaptation of vehicle schedules and systematically develops and evaluates innovative ideas for the management of transportation processes in volatile scenarios. Showing the progress made in the development of the methodological toolbox for decision support in dynamic process management is the major motivation behind this book. The result is a new integrated approach to dynamic decision making. Existing process planning approaches for volatile environments and their application boundaries are investigated in Part I. Part II introduces the concept of feedback-controlled adaptive decision models and proposes the required extensions of the online decision making framework and of multi-agent systems. A comprehensive evaluation of the proposed decision model adaptation framework based on computational simulation experiments is reported in Part III and demonstrates the predominance of the new approach. Distinguishing features of this book are: -It provides the first contribution to the operational management of processes in supply networks that explicitly addresses the two challenges of dynamics and distributed decision making simultaneously. -It systematically approaches the limits of model-based process planning but also proposes methods to extend the application boundaries. -Software prototypes are developed and a comprehensive evaluation within numerical simulation experiments is executed. -The observed results are discussed with an explicit focus on specific performance indicators (flexibility, stability and robustness). -The strict interdisciplinary approach merging the requirements and needs of management sciences, operations research and computer sciences is pursued throughout the book.

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Product Description

This monograph presents results originating from a research project investigating autonomous adaptation of vehicle schedules and systematically develops and evaluates innovative ideas for the management of transportation processes in volatile scenarios. Showing the progress made in the development of the methodological toolbox for decision support in dynamic process management is the major motivation behind this book. The result is a new integrated approach to dynamic decision making. Existing process planning approaches for volatile environments and their application boundaries are investigated in Part I. Part II introduces the concept of feedback-controlled adaptive decision models and proposes the required extensions of the online decision making framework and of multi-agent systems. A comprehensive evaluation of the proposed decision model adaptation framework based on computational simulation experiments is reported in Part III and demonstrates the predominance of the new approach. Distinguishing features of this book are: -It provides the first contribution to the operational management of processes in supply networks that explicitly addresses the two challenges of dynamics and distributed decision making simultaneously. -It systematically approaches the limits of model-based process planning but also proposes methods to extend the application boundaries. -Software prototypes are developed and a comprehensive evaluation within numerical simulation experiments is executed. -The observed results are discussed with an explicit focus on specific performance indicators (flexibility, stability and robustness). -The strict interdisciplinary approach merging the requirements and needs of management sciences, operations research and computer sciences is pursued throughout the book.

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Product Details

General

Imprint

Springer-Verlag New York

Country of origin

United States

Series

Operations Research/Computer Science Interfaces Series, 50

Release date

May 2011

Availability

Expected to ship within 10 - 15 working days

First published

2011

Authors

Dimensions

235 x 155 x 12mm (L x W x T)

Format

Hardcover

Pages

184

Edition

2011 ed.

ISBN-13

978-1-4419-9681-7

Barcode

9781441996817

Categories

LSN

1-4419-9681-8



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