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Journal ArticleDOI

Negotiation-Based Collaborative Planning in Divergent Two-Tier Supply Chains

18 Jan 2007-International Journal of Production Research (Taylor & Francis)-Vol. 45, Iss: 2, pp 465-484
TL;DR: In this paper, the authors describe a negotiation-based process to synchronize plans between independent partners of a two-tier supply chain consisting of one supplier and several buyers, and show how modified versions of these models can be utilized to support the negotiation process by evaluating given purchasing orders or supplies and by generating counter-proposals.
Abstract: Advanced Planning Systems are based on the principles of hierarchical planning, which—at least at the top level—grounds on centralized planning. However, central coordination requires access to all relevant information and the power to impose planning results on all organizational units. In consequence it can be realized only for parts of an inter-organizational supply chain, and the question arises whether there exist alternate ways to achieve coordination. In this paper we describe a non-hierarchical, negotiation-based process, which can be used to synchronize plans between independent partners of a two-tier supply chain consisting of one supplier and several buyers. Assuming that all partners generate plans based upon mathematical programming—as in most Advanced Planning Systems at the master planning level—we show how modified versions of these models can be utilized to support the negotiation process by evaluating given purchasing orders or supplies and by generating counter-proposals. Resulting is a...

Summary (2 min read)

1 Introduction

  • Coordinated planning and control of operations, i.e. production, storage, and distribution processes, is a central element of Supply Chain Management (SCM) (Stadtler (2005)).
  • Without any coordinating action, all parties, i.e. each buyer and the supplier, use their planning model with local information only (local optimization).
  • A summary and final remarks conclude the paper.

2 Planning model

  • Based on the SC setting described above and shown in figure 1, the authors assume that each SC partner uses a multi-level capacitated lot-sizing problem (MLCLSP, e.g. Stadtler (2003)) to generate his local MPS.
  • Neglecting setup times and lead times, the MLCLSP can be formulated as follows: Model 1 MLCLSP.

TtMmoCxa tmtmtj

  • Thereby, each partner uses her/his set of input parameters (e.g. J, M, Cm,t, am,j), including a local demand forecast Dj,t, and obtains local plan results (e.g. xj,t, ij,t).
  • For the sake of simplicity the authors assume that all partners use an identical planning horizon of T periods.
  • Since such completely isolated planning yields sub-optimal SC performance as explained above, the question arises how the isolated planning models can be linked to achieve coordination and thus improved SC performance.
  • One approach to achieve this linkage without fully centralized control is described in the next section.

3 Model-Based Negotiations

  • In this section the authors describe the model-based negotiation scheme.
  • Assuming that each buyer k has announced order quantities XOk,j,t, constraints (3.19) and (3.20) are used to incorporate the order proposals into the supplier’s planning situation.
  • First, the cost increase above each buyer’s locally optimal plan of accepting the supplier’s last supply proposal (CB,kprop,i-1) and second the cost increase associated with their current counterproposal (CB,kcomp,i).
  • In addition, a share of the supplier’s remaining net savings, e.g. a fixed reward for joining the negotiation, should be spread among the buyers for ensuring that each SC partner gains a true advantage.

4 Computational Results

  • The performance of the negotiation scheme is explored with an automated version of the negotiation process.
  • Available resource capacity, which is input to the planning models (constraints (2.4)), is calculated from the average capacity requirement based on the final demand series and the utilization factors given in Table 2.
  • For the remaining 190 test instances the best solution detected after 1200 sec. is used as reference value.
  • This variation is primarily caused by test instances whose upstream planning solution is already relatively close the lower benchmark; e.g. about 20% have gaps to central planning of less than 5% as shown in Figure 3.
  • Thus, despite the fact that the average cost gap of negotiations to central planning is particularly high in class 3B as shown in Table 3, the negotiation scheme performs constantly well (or even better in case of 3B) in bringing the initial upstream result closer to the benchmark solution of central planning.

5 Conclusions

  • In summary, this paper describes a negotiation-based scheme for collaborative planning in two-tier SCs comprising a single supplier and several buyers.
  • It rests on the approach developed for two SC partners in Dudek / Stadtler (2004) and extends the negotiation mechanism to cover multiple buyers.
  • Compensation and savings share can be incorporated into given contract terms as a bonus, granted when a buyer complies with negotiated order quantities.
  • The scheme leaves a limited opportunity for opportunistic behavior, especially at the buyers’ side.

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Negotiation-Based Collaborative Planning in Divergent
Two-Tier Supply Chains
Gregor Dudek, Hartmut Stadtler
To cite this version:
Gregor Dudek, Hartmut Stadtler. Negotiation-Based Collaborative Planning in Divergent Two-Tier
Supply Chains. International Journal of Production Research, Taylor & Francis, 2007, 45 (02), pp.465-
484. �10.1080/00207540600584821�. �hal-00512887�

For Peer Review Only
Negotiation-Based Collaborative Planning in Divergent Two-
Tier Supply Chains
Journal:
International Journal of Production Research
Manuscript ID:
TPRS-2005-IJPR-0234.R1
Manuscript Type:
Original Manuscript
Date Submitted by the
Author:
20-Nov-2005
Complete List of Authors:
Dudek, Gregor; Darmstadt University of Technology, Department of
Production and Supply Chain Management
Stadtler, Hartmut; University of Hamburg, Institute of Logistics and
Transport
Keywords:
MATH PROGRAMMING, SUPPLY CHAIN MANAGEMENT
Keywords (user):
Collaborative Planning
http://mc.manuscriptcentral.com/tprs Email: ijpr@lboro.ac.uk
International Journal of Production Research

For Peer Review Only
Authors
Gregor Dudek
Holzstrasse 14
Mainz, 55116, Germany
Darmstadt University of Technology
Department of Production and Supply Chain
Management
Phone + 49 170 334 2355
Email: gregor.dudek@gmx.de
Hartmut Stadtler
Von-Melle-Park 5
Hamburg, 20146, Germany
University of Hamburg
Institute of Logistics and Transport
Phone: +49 40 4 28 38-2609
Fax: +49 40 4 28 38-6283
Email: hartmut.stadtler@uni-hamburg.de
Total word count main text: ~ 6.400
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For Peer Review Only
Negotiations-Based Collaborative Planning in Divergent Two-Tier Supply Chains 2
Negotiation-Based Collaborative Planning in
Divergent Two-Tier Supply Chains
Abstract
Advanced Planning Systems are based on the principles of hierarchical planning, which – at
least at the top level – grounds on centralized planning. However, central coordination
requires access to all relevant information and the power to impose planning results on all
organizational units. In consequence it can be realized only for parts of an inter-organizational
supply chain, and the question arises whether there exist alternate ways to achieve
coordination.
In this paper we describe a non-hierarchical, negotiation-based process, which can be used to
synchronize plans between independent partners of a two-tier supply chain consisting of one
supplier and several buyers. Assuming that all partners generate plans based upon
mathematical programming – as in most Advanced Planning Systems at the master planning
level – we show how modified versions of these models can be utilized to support the
negotiation process by evaluating given purchasing orders or supplies and by generating
counter-proposals. Resulting is an iterative, negotiation-like scheme, which establishes and
subsequently improves a consistent overall plan based on a limited exchange of information
between the supply chain partners.
Key Words: Collaborative Planning, Supply Chain Management, Mathematical
Programming
1 Introduction
Coordinated planning and control of operations, i.e. production, storage, and distribution
processes, is a central element of Supply Chain Management (SCM) (Stadtler (2005)).
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For Peer Review Only
Negotiations-Based Collaborative Planning in Divergent Two-Tier Supply Chains 3
One approach to coordinate operations is by centralized planning. Proponents of this approach
usually suggest to implement hierarchical planning such that centralized coordination happens
at a medium-term level, whereas it is left to the owners of the distinct operational processes to
implement the results at the level of short-term planning and control (Shapiro (1999), Rohde /
Meyr / Wagner (2000)).
However, centralized planning requires access to all relevant information. Moreover, it can
fail simply because individual partners are involved in several SCs; for example suppliers
typically serve more than a single customer. Therefore, alternate approaches are required
which establish synchronized operations based on the exchange of few information and an
acceptable coordination effort (e.g. Kilger / Reuter (2005)).
This paper provides such an alternate approach by laying out a negotiation-based process for
aligning operations in a SC comprising several buyers and one common supplier as shown in
Figure 1. Thereby, we focus on the medium-term task of Master Production Scheduling
(MPS) (e.g. Silver / Pyke / Peterson (1998)) or Master Planning (Rohde / Meyr / Wagner
(2000)).
We assume that several end products are sold by each buyer based on dynamic, but
deterministic (or forecasted) demand by period. Each buyer’s operations may comprise
multiple stages and require a set of components that are purchased from the supplier. The
supplier too may face a multi-stage production process. We suppose information is fully
asymmetric, i.e. without additional communication each partner only possesses local
information on his own operations and a local demand forecast. The supplier forecasts the
demand of his end-products based on his best guess of the buyers’ need of input materials. All
partners are assumed to generate their local MPS with mathematical programming models.
Without any coordinating action, all parties, i.e. each buyer and the supplier, use their
planning model with local information only (local optimization). Such isolated planning and
operation typically results in poor performance with unnecessarily high costs, large inventory
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Citations
More filters
Journal ArticleDOI
TL;DR: A recursion-based order negotiation model which can be used to modify orders in the cooperation of the buyer and supplier according to their external orders, available resources and inventory, and for generating optimal results as obtained by supply chain system coordination is proposed.
Abstract: The order negotiation are regular activities for a synergic operations planning between supply chains partners. As operations planning can usually be realized only for isolated parts of an overall supply chain, the question arises whether there are alternative negotiation ways of synergic operations planning. In this paper we propose a recursion-based order negotiation model which can be used to modify orders in the cooperation of the buyer and supplier according to their external orders, available resources and inventory, and for generating optimal results as obtained by supply chain system coordination. Three scenarios emerge in the application of the model: the solution is in the solution set (orders can be accepted by the other party); the solution is in the solution set, but cannot be further optimized; the solution is completely out of the solution set (called order conflicts). And under the three scenarios, we provide the corresponding solutions, especially for the order-conflict scenario. First, find an initial relaxation solution that minimizes overall cost of the supply chain as the reference solution. Second, maximize the utilization of production with a simulation optimization method to increase the purchase order. Then find an optimal solution which balance the supply and demand of both sides. Finally, the validity of the order negotiation model is verified in various situations by computational tests.

Cites background from "Negotiation-Based Collaborative Pla..."

  • ...In this paper, it is defined as the order conflict, When there is no intersections [7-10] ....

    [...]

Book ChapterDOI
14 Aug 2017
TL;DR: This paper tries to overcome deadlocks during automated single negotiation text by using compensation payments and suggests that the negotiation results are both superior and faster compared to an ANM without compensation payments.
Abstract: Automated negotiation mechanisms (ANMs) can be used to semi-automatically negotiate well-structured but complex contracts. Such negotiations among multiple negotiators, who are represented by software agents, can easily reach a deadlock because they block each others proposals. This of course leads to inferior results. Our aim is to improve the performance of ANMs. In this paper, we try to overcome deadlocks during automated single negotiation text by using compensation payments. Compensation payments are calculated by a mediator according to the Nucleolus method from cooperative game theory. It guarantees that a unique payment is calculated in any case. Furthermore, it lies in the Core, if the Core exists. The proposed ANM can be vulnerable against shading the desired compensation payments. However, our computational experiments suggest that the negotiation results are both superior and faster compared to an ANM without compensation payments. The dominance increases with an increasing number of negotiators.
Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper conducted a comprehensive review of analytical modeling SCM studies in C-Commerce, aiming at providing guidance on what it is, what to do, and how to do.
Journal ArticleDOI
TL;DR: The aim is to study how negotiation based planning processes would be used to refine locally preferred ordering patterns, which would affect the overall performance of the supply chain in terms of costs and service level.
Abstract: This paper focuses on a negotiation based collaborative planning process for the determination of order lot-size over multi-period planning, and confined to a two-tier supply chain scenario. The aim is to study how negotiation based planning processes would be used to refine locally preferred ordering patterns, which would consequently affect the overall performance of the supply chain in terms of costs and service level. Minimal information exchanges in the form of mathematical models are suggested to represent the local preferences and used to support the negotiation processes.
Book ChapterDOI
01 Jan 2010
TL;DR: Apart from the identification of improved solutions within an acceptable number of iterations, a further requirement for practicable coordination schemes is their applicability by rational, self-interested parties, which implies that the schemes can be embedded into suitable coordination mechanisms.
Abstract: Apart from the identification of improved solutions within an acceptable number of iterations, a further requirement for practicable coordination schemes is their applicability by rational, self-interested parties, which implies that the schemes can be embedded into suitable coordination mechanisms.
References
More filters
Book
01 Jan 1998
TL;DR: In this paper, the authors present a framework for inventory management and production planning and scheduling with a focus on the most important (Class A) and routine (Class C) items.
Abstract: THE CONTEXT AND IMPORTANCE OF INVENTORY MANAGEMENT AND PRODUCTION PLANNING AND SCHEDULING. The Importance of Inventory Management and Production Planning and Scheduling. Strategic Issues. Frameworks for Inventory Management and Production Planning and Scheduling. Forecasting. TRADITIONAL REPLENISHMENT SYSTEMS FOR MANAGING INDIVIDUAL--ITEM INVENTORIES. Order Quantities When Demand is Approximately Level. Lot Sizing for Individual Items with Time--Varying Demand. Individual Items with Probabilistic Demand. SPECIAL CLASSES OF ITEMS. Managing the Most Important (Class A) Inventories. Managing Routine (Class C) Inventories. Style Goods and Perishable Items. THE COMPLEXITIES OF MULTIPLE ITEMS AND MULTIPLE LOCATIONS. Coorinated Replenishments at a Single Stocking Point. Supply Chain Management and Multiechelon Inventories. PRODUCTION PLANNING AND SCHEDULING. An Overall Framework for Production Planning and Scheduling. Medium--Range Aggregate Production Planning. Material Requirements Planning and its Extensions. Just--in--Time and Optimized Production Technology. Short--Range Production Scheduling. Summary. Appendices. Indexes.

2,739 citations


"Negotiation-Based Collaborative Pla..." refers methods in this paper

  • ...Thereby, we focus on the medium-term task of Master Production Scheduling (MPS) (e.g. Silver et al. 1998) or Master Planning (Rohde et al. 2000)....

    [...]

Book ChapterDOI
TL;DR: This chapter extends the newsvendor model by allowing the retailer to choose the retail price in addition to the stocking quantity, and discusses an infinite horizon stochastic demand model in which the retailer receives replenishments from a supplier after a constant lead time.
Abstract: Publisher Summary This chapter reviews the supply chain coordination with contracts. Numerous supply chain models are discussed. In each model, the supply chain optimal actions are identified. The chapter extends the newsvendor model by allowing the retailer to choose the retail price in addition to the stocking quantity. Coordination is more complex in this setting because the incentives provided to align one action might cause distortions with the other action. The newsvendor model is also extended by allowing the retailer to exert costly effort to increase demand. Coordination is challenging because the retailer's effort is noncontractible—that is, the firms cannot write contracts based on the effort chosen. The chapter also discusses an infinite horizon stochastic demand model in which the retailer receives replenishments from a supplier after a constant lead time. Coordination requires that the retailer chooses a large basestock level.

2,626 citations


"Negotiation-Based Collaborative Pla..." refers background in this paper

  • ...Cachon (2003) deals with a setting where the buyers compete for the total market demand....

    [...]

  • ...Tsay 1999 , Lariviere and Porteus 2001 , Cachon 2003 ), lot-sizing problems in a two-party setting (e....

    [...]

  • ...In the following we limit our attention to the particular setting considered here, namely a SC consisting of one supplier and several buyers (for a more broad literature review refer to, e.g. Thomas and Griffin 1996, Erengüc et al. 1999, Tsay et al. 1999, Cachon 2003)....

    [...]

  • ...Publications deal, e.g. with the classical newsvendor problem (see e.g. Tsay 1999, Lariviere and Porteus 2001, Cachon 2003), lot-sizing problems in a two-party setting (e.g. Monahan 1984, Weng 1995), or serial, multi-stage SCs (Chen 1999, Lee and Whang 1999)....

    [...]

Book
05 May 1993

2,454 citations

Journal ArticleDOI
TL;DR: In traditional supply chain inventory management, orders are the only information firms exchange, but information technology now allows firms to share demand and inventory data quickly and inexpensively, and it is concluded that implementing information technology to accelerate and smooth the physical flow of goods through a supply chain is significantly more valuable.
Abstract: In traditional supply chain inventory management, orders are the only information firms exchange, but information technology now allows firms to share demand and inventory data quickly and inexpensively. We study the value of sharing these data in a model with one supplier, N identical retailers, and stationary stochastic consumer demand. There are inventory holding costs and back-order penalty costs. We compare a traditional information policy that does not use shared information with a full information policy that does exploit shared information. In a numerical study we find that supply chain costs are 2.2% lower on average with the full information policy than with the traditional information policy, and the maximum difference is 12.1%. We also develop a simulation-based lower bound over all feasible policies. The cost difference between the traditional information policy and the lower bound is an upper bound on the value of information sharing: In the same study, that difference is 3.4% on average, and no more than 13.8%. We contrast the value of information sharing with two other benefits of information technology, faster and cheaper order processing, which lead to shorter lead times and smaller batch sizes, respectively. In our sample, cutting lead times nearly in half reduces costs by 21% on average, and cutting batches in half reduces costs by 22% on average. For the settings we study, we conclude that implementing information technology to accelerate and smooth the physical flow of goods through a supply chain is significantly more valuable than using information technology to expand the flow of information.

1,790 citations


"Negotiation-Based Collaborative Pla..." refers background in this paper

  • ...For example, Cachon and Fisher (2000) study the value of information sharing when N identical buyers face stationary stochastic demand for a single product which they replenish from the supplier....

    [...]

Journal Article
TL;DR: In this article, the authors identify four major causes of the bullwhip effect: demand forecast updating, rationing, price fluctuation, and shortage games, and they suggest several ways in which companies can counteract the effect.
Abstract: Tremendous variability in orders along the supply chain can plague companies trying to eliminate excess inventory, forecast product demand, and simply make their supply chain more efficient. What causes the bullwhip effect that distorts information as it is transmitted up the chain? The authors identify four major causes: 1. Demand forecast updating. As each entity along the chain places an order, it replenishes stock and includes some safety stock. With long lead times, there may be weeks of safety stocks, which make the fluctuation in demand more significant. 2. Order batching. Companies may place orders in batches, often to avoid the cost of processing orders more frequently or the high transportation costs for less-than-truckload orders. Suppliers, in turn, face erratic streams of orders, and the bullwhip effect occurs. When order cycles overlap, the effect is even more pronounced. 3. Price fluctuation. Special promotions and price discounts result in customers buying in large quantities and stocking up. When prices return to normal, customers stop buying. As a result, their buying pattern does not reflect their consumption pattern. 4. Rationing and shortage gaming. If product demand exceeds supply, a manufacturer may ration its products. Customers, in turn, may exaggerate their orders to counteract the rationing. Eventually, orders will disappear and cancellations pour in, making it impossible for the manufacturer to determine the real demand for its product. The authors suggest several ways in which companies can counteract the bullwhip effect: 1. Avoid multiple demand forecast updates. Companies can make demand data from downstream available upstream. Or they can bypass the downstream site by selling directly to the consumer. Also, they can improve operational efficiency to reduce highly variable demand and long resupply lead times. 2. Break order batches. Companies can use electronic data interchange to reduce the cost of placing orders and place orders more frequently. And they can ship assortments of products in a truckload to counter high transportation costs or use third-party logistics companies to handle shipping. 3. Stabilize prices. Manufacturers can reduce the frequency and level of wholesale price discounting to prevent customers from stockpiling. They can also use activity-based costing systems so they can recognize when companies are buying in bulk. 4. Eliminate gaming in shortage situations. In shortages, suppliers can allocate product based on past sales records, rather than on orders, so customers don't exaggerate their orders. They can also eliminate their generous return policies, so retailers are less likely to cancel orders. Only by thoroughly understanding the underlying causes of the bullwhip effect, say the authors, can companies counteract and control it.

1,565 citations