Supply chain coordination mechanisms new approaches for collaborative planning

Lecture Notes in Economics and Mathematical Systems Founding Editors: M Beckmann H.P Künzi Managing Editors: Prof Dr G Fandel Fachbereich Wirtschaftswissenschaften Fernuniversität Hagen Feithstr 140/AVZ II, 58084 Hagen, Germany Prof Dr W Trockel Institut für Mathematische Wirtschaftsforschung (IMW) Universität Bielefeld Universitätsstr 25, 33615 Bielefeld, Germany Editorial Board: A Basile, H Dawid, K Inderfurth, W Kürsten 628 Martin Albrecht Supply Chain Coordination Mechanisms New Approaches for Collaborative Planning ABC Dr Martin Albrecht PAUL HARTMANN AG martin.albrecht@hartmann.info ISSN 0075-8442 ISBN 978-3-642-02832-8 e-ISBN 978-3-642-02833-5 DOI 10.1007/978-3-642-02833-5 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2009931327 c Springer-Verlag Berlin Heidelberg 2010 This work is subject to copyright All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer Violations are liable to prosecution under the German Copyright Law The use of general descriptive names, registered names, trademarks, etc in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use Cover design: SPi Publisher Services Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com) For Rita and Amalia Isabel Foreword Inter-organizational supply chains have to coordinate their material, information, and financial flows efficiently to be competitive However, legally independent supply chain (SC) partners are often reluctant to share critical data such as costs or capacity utilization, which is a prerequisite for central planning or hierarchical planning – the planning paradigm of today’s Advanced Planning Systems (APS) Consequently, concepts for collaborative planning are needed, considering a joint decision making process for aligning plans of individual SC members with the aim of achieving coordination in the light of information asymmetry This is the starting point and challenge of the PhD thesis of Martin Albrecht because little is known about how to design a solution for this difficult decision problem Starting from an initial solution – that may be generated by upstream planning – improved solutions are looked for This is achieved by computer-supported negotiations, i.e., an exchange of different order proposals within the planning interval among the SC partners involved, where partners are free to accept or reject proposals One challenge in this negotiation process is to find new proposals and counterproposals which have a good chance of acceptance while improving the competitive position of a SC as a whole Here, Albrecht devised new generic coordination schemes for planning tasks which can be modeled either by Linear Programming (LP) or Mixed Integer Linear Programming For the LP case finite convergence to the optimum has been proved While previous research on collaborative planning stopped with a clever coordination scheme Albrecht also considered a further, very important aspect of negotiations: How to get the partners to tell the truth when exchanging information and to accept a very promising solution for the supply chain as a whole Formally speaking, coordination mechanisms are needed where the coordination schemes can be embedded One of the coordination mechanisms advocated by Albrecht is the surplus sharing by an initially agreed upon lump sum payment to one party He has been able to show that the corresponding mechanism results in truth-telling as a weakly dominant strategy The reader can expect both analytical results as well as computational tests of collaborative planning schemes for various lot-sizing problems including some from industrial practice – and there is a lot more to be gained vii viii Foreword from reading this thesis but I will not reveal more details here I wish this excellent thesis a wide audience of interested and very satisfied readers and a large impact on collaborative planning Hamburg, April 2009 Hartmut Stadtler Preface When I started my research, most known collaborative planning approaches dealing with mathematical programming models were based on a serious oversimplification of reality: They presumed a team setting, where parties honestly disclose information and sometimes even accept deteriorations if this benefits the supply chain as a whole One of the major contributions of this work has been to relax this assumption I have developed mechanisms, which achieve coordination despite self-interested behavior of parties Without wanting to relativize the importance of this contribution, I would like to point out the existence of a particular real-world team: The people supporting me when I was writing this thesis First of all, I am indebted to Prof Dr Hartmut Stadtler He not only set the example for my research, but also provided (sometimes incredibly) generous advice and professional and personal support Among many other things, he has patiently read my papers many times and supplied several insightful suggestions at all stages of this work I am also grateful to Prof Dr Karl-Werner Hansmann for his willingness to serve as the co-referee for this thesis Apart from my academic advisers, I am indebted to my colleagues and collaborating researchers Particularly, I want to thank Carolin Păuttmann for her great teamwork in the EU-project InCoCo-S, for listening to many of my (not always fully worked out) ideas, and for carefully proofreading the whole dissertation Dr Bernd Wagner and Volker Windeck also read parts of the thesis and provided many valuable suggestions Last, but not least, I am thankful to Prof Dr Heinrich Braun and Benedikt Scheckenbach from the SAP AG for challenging discussions and for making available the real-world test data used in this work I also thank the Gesellschaft făur Logistik und Verkehr for subsidizing the printing of this work Certainly most important for this dissertation has been my family, although not interested in supply chain management at all My parents supported my education, without expecting anything in return My wife Rita not only renounced to much shared time, but encouraged me with all her love to keep on researching until I have (finally) been satisfied with this work Thank you, everybody Heidenheim, May 2009 Martin Albrecht ix Chapter Summary and Outlook This thesis has proposed new supply chain coordination mechanisms, which incorporate a number of characteristics favoring their applicability in practice The mechanisms can coordinate plans generated on the basis of complex mathematical programming models on behalf of self-interested parties holding private information, and not require the participation of a third party In the literature, all of these characteristics have been regarded as important, but they have never been covered within a single approach An introduction to the research problem tackled by this thesis is given in Chap There, we have presented mathematical models for (intra-organizational) mid-term supply chain planning (Master Planning) as well as basic definitions that are used throughout this work Moreover, we have shown how to model inter-organizational planning processes formally Last, we have determined drivers for suboptimalities without coordination, which, e.g., result from the application of myopic procedures such as upstream planning Chapter provides a review of the state-of-the-art in supply chain coordination In contrast to existing surveys, which focus on specific types of mechanisms, our review covers the whole spectrum of the related literature The mechanisms and the underlying ideas are described separately according to the assumptions on parties’ information statuses (no, unilateral, or multilateral information asymmetry) and the concepts from game theory the mechanisms rely on The coordination mechanisms presented in Chaps and constitute the principal contribution of this work Two main tasks have to be resolved by them: The identification of coordinated solutions, i.e., systemwide improvements compared to a given initial solution, and the determination of incentives for their implementation In Chap 4, several coordination schemes have been devised that identify coordinated solutions for a broad range of Master Planning problems and cover different requirements on the information exchange At first, we have developed two variants of a generic scheme, which can be applied for coordinating linear programming (LP) models in arbitrarily structured decentralized organizations In this scheme, parties iteratively exchange proposals about the use of the central resources (i.e., supply quantities in supply chains) Depending on the mechanism the scheme is embedded in, the cost effects to these proposals are either reported iteratively by all but one decentralized party or M Albrecht, Supply Chain Coordination Mechanisms: New Approaches for Collaborative Planning, Lecture Notes in Economics and Mathematical Systems 628, DOI 10.1007/978-3-642-02833-5 7, c Springer-Verlag Berlin Heidelberg 2010 197 198 Summary and Outlook simultaneously disclosed by all parties We have shown by analytical proofs that both variants are able to identify the systemwide optimum in a finite number of iterations, provided that the decentralized problems can be formulated as LP models The variant with an iterative exchange of cost changes is even able to identify the systemwide optimum if one decentralized model is of a mixed-integer programming (MIP) type The second scheme developed in this work aims to coordinate supply chains consisting of one buyer and one or multiple suppliers planning based on multi-level uncapacitated lot-sizing problems (MLULSP) This scheme also relies on the exchange of supply proposals, but – in contrast to the generic scheme – does not require specific assumptions on the exchange of cost changes We can show that the maximum number of proposals generated increases linearly with the number of periods and the number of the items supplied For the special case of time-invariant end item demand, zero initial inventories, and the production portfolio of the buyer limited to one item, we have derived an upper bound on the maximum gap between the systemwide optimum and the best solution identified by this scheme Moreover, we have shown how to adapt the schemes for an effective coordination of Master Planning in two-tier supply chains First, the generic scheme for LP has been customized for coordinating Master Planning among two parties Second, we have presented modifications that improve the convergence and allow an application of this scheme to MIP models Third, we have devised extensions that effectively coordinate decentralized models with capacitated lot-sizing, voluntary compliance by the supplier, lost sales, and multiple suppliers involved in the coordination For each of the schemes, extensive numerical tests have been conducted based on randomly generated test instances The results of these tests have been reported in Chap In all settings considered, the systemwide costs have been significantly reduced compared to upstream planning after 10 or 20 iterations For small problem sizes or specific model classes (e.g., the MLULSP), near optimal solutions can be obtained For the campaign planning models, the scheme can even identify improvements over the solutions to the centralized model that have been found after a given time limit, which is two times the limit for running the scheme on average In addition, we have tested the performance of the scheme for real-world data originating from customers of the SAP AG Although these data comprise additional constraints like storage capacity and transportation lot size restrictions and involve huge model sizes, the scheme was able to identify significant improvements Apart from the identification of improved solutions, the second task to be tackled by a coordination mechanism is the establishment of incentives for the implementation of these solutions For this purpose, we have presented in Chap three different contractual frameworks, where the schemes can be embedded First, the sharing of the surplus can solely be determined by the party that does not report its cost changes during the execution of the scheme For an efficient coordination, fair and truthful behavior by all parties is required then Fairness, however, has only been observed to a certain degree in behavioral experiments In spite of that, we believe that this mechanism can be employed in organizational structures where one dominant party carries out auditing measures like open-book accounting Summary and Outlook 199 Second, we have devised a contractual framework where truthful cost reporting is a Nash equilibrium for parties There, the surplus is shared such that the costreporting parties obtain lump-sum payments, while one party (which pays these lump sums) receives the remaining share of the surplus Analyzing parties’ best strategies in this mechanism under the assumption of prior incomplete knowledge about the surplus, a lower bound on the efficiency of this framework has been derived: For two parties and uniformly distributed prior knowledge, the efficiency exceeds 75% on average Third, the surplus can be shared by a sealed bid double auction Here, parties simultaneously submit their costs changes in form of sealed bids for all proposals generated and implement the proposals with the lowest systemwide costs The surplus is shared equally among parties Again, a lower bound on the efficiency of this auction can be derived Finally, we have outlined how the mechanisms can be adapted if production planning is based on rolling schedules Summarizing, the schemes and mechanisms proposed form generic, innovative concepts for collaborative supply chain planning and include a series of features favoring practical applications Given the existence of an effective scheme, the mechanisms can be applied for coordinating any decisions in decentralized systems The generic scheme is able to identify the systemwide optimum for any decentralized LP models within a finite number of steps The applicability of (a modified version) of this scheme to Master Planning problems of one buyer and one or several suppliers including binary variables has been shown by the computational study of this work An investigation of the transferability of the schemes to other economic decision problems seems worthwhile This way has been pursued by Păuttmann (2007),1 who adapts the generic scheme to the coordination of intermodal freight transportation Apart from transportation, other potential applications are in areas like production scheduling and controlling, where the cost allocation for several agents sharing a common resource has to be resolved, as well as different organizational structures like three-tier supply chains Furthermore of interest is the determination of the problem classes for which the scheme proposed constitutes an effective heuristic (like for multi-level campaign planning problem with batch size restrictions) Challenges for future research are analyses of the actions of parties using repeatedly the mechanisms proposed As mentioned in Chap 5, learning and signaling strategies have to be taken into account then, which considerably augments the complexity of the resulting modeling Both laboratory research to evaluate the empirical behavior of parties and analytical 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(2005, p 17) For similar representations, see, e.g., Shapiro (2001, p 6) and Stadtler (2007b, p 10) M Albrecht, Supply Chain Coordination Mechanisms: New Approaches for Collaborative Planning, Lecture... Heidelberg 2010 Supply Chain Planning and Coordination Fig 2.1 Sketch of a supply chain (example) competitiveness of a supply chain as a whole.”3 One of the building blocks of supply chain management... 2.3.3 Upstream Vs Collaborative Planning 5 10 12 20 20 24 30 Coordination Mechanisms for Supply Chain Planning 3.1 Symmetric Information