Negotiation-based collaborative planning between supply chains partners

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Abstract

It is often proposed that operations planning in supply chains can be organized in terms of a hierarchical planning system. However, the hierarchical approach assumes a single, centralized planning task for synchronizing operations across the supply chain. As central coordination can usually be realized only for isolated parts of an overall supply chain, the question arises whether there are alternative ways of coordination.

In this paper we propose a non-hierarchical, negotiation-based scheme which can be used to synchronize plans between two independent supply chain partners linked by material flows. Assuming that plans are generated based upon mathematical programming models, we show how modified versions of these models can be utilized for evaluating material orders or supplies proposed by the supply chain partner and for generating counter-proposals. Resulting is an iterative, negotiation-like process which establishes and subsequently improves a consistent overall plan. Computational tests suggest that the scheme comes close to optimal results as obtained by central coordination.

Introduction

Supply chain management (SCM) deals with the management of the multiple relationships across the supply chain, i.e. the network of organizations involved in creating final customer products and services (Christopher, 1998). As such, SCM embraces various business processes which are of relevance for servicing customers (e.g. order fulfillment, customer service management, product development) and explicitly accounts for the structure of the supply chain (SC) (Cooper et al., 1997).

Planning and control of operations, i.e. production, storage, and distribution processes, across the SC clearly forms a key aspect of SCM. Rohde et al. (2000) identified the various planning tasks of interest and showed how they can be organized in terms of a hierarchical planning structure, the supply chain planning matrix (Fig. 1).

At the operational planning level the task of master planning (MP) plays a crucial role. It serves to balance supply with demand over the planning horizon and to synchronize operations across the SC (Rohde and Wagner, 2002). In order to achieve this purpose, a single centralized planning task is proposed for the entire SC as indicated in Fig. 1. The implementation of a centralized MP however requires a high degree of integration among participating organizational units. In practice, centralized MP can therefore only be realized for relatively small, isolated parts of the SC, such as for entities belonging to a single company.

Thus, the question arises of how to link and coordinate planning between these isolated parts of the SC. This paper contributes to the question in laying out a negotiation-like coordination scheme for two parties, a buyer and a supplier, which establishes and subsequently improves a consistent overall plan.

The coordination process of autonomous, yet inter-connected MP activities is referred to as collaborative planning (CP) in the following. The integrated parts of the SC for which centralized MP is realized are called planning domains (in analogy to Kilger and Reuter, 2002). The resulting situation is depicted in Fig. 2. It shows the facility networks pertaining to each planning domain and the corresponding planning processes. Within each planning domain, centralized MP takes place and coordinates subsequent, short-term planning activities. In absence of any supply chain integration each MP task is accomplished with an isolated view of the corresponding domain and based on local demand forecasts. However, since operations at the distinct domains actually interrelate due to supplies required at the buyer domain, uncoordinated planning results in sub-optimization and inefficiencies such as unnecessary inventory buffers or frequent plan adjustments.

Therefore, to improve supply chain performance, domain-specific MP tasks can be linked by CP. The scheme developed in the following assumes that mathematical programming models are used for domain-specific MP. The idea is to pass order proposals (generated by the buyer) and supply proposals (generated by the supplier) as well as associated cost effects between the parties in an iterative manner. A proposal received from the partner is analyzed for its consequences on local planning, and a counter-proposal is generated by introducing partial modifications. Resulting is a negotiation-like process which subsequently improves supply chain wide costs without centralized decision making and with limited exchange of information between the partners. Specifically, only the respective order/supply proposals and associated effects on local cost are exchanged.

The paper is organized as follows. A literature review is presented in the next section. Thereafter, we further detail the decision situation outlined above and introduce a quantitative modeling framework. The CP coordination scheme is described in Section 4, followed by computational results which demonstrate its performance in Section 5. A summary and some final remarks conclude the paper.

Section snippets

Literature review

Relevant literature originates from several fields of contemporary research on SCM. First, there is a large and growing stream of literature on SC coordination by contracts. An often studied situation within this context is the news vendor problem where a retailer faces random demand and has to buy a certain quantity from the manufacturer prior to the realization of demand (e.g. Silver et al., 1998; Lariviere and Porteus, 2001). Another class of papers is concerned with individual and SC wide

Decision situation and modeling

In this section we outline the model assumed being used for intra-domain master planning. Also, links to adjacent planning domains will be explicitly considered by additional constraints, so that the model can be employed to collaborative planning.

As mentioned above, master planning serves to synchronize operations and material flows across the SC at a medium term such that market demands are met at minimum cost. Planning decisions may concern purchasing, production, transportation, and

Collaborative planning scheme

In this section we present the negotiation-based scheme for collaborative planning. Thereby, the planning model presented above is utilized throughout every stage of the process.

The following section gives an overview of the coordination process in question. Thereafter, the process steps carried out by buyer and supplier in each iteration are described in more detail. Section 4.3 is concerned with the total process flow and financial implications resulting from the negotiation scheme.

Computational results

Computational tests have been conducted and are discussed in the following in order to explore the performance of the CP scheme. Thereby, the team approach with correct announcement of cost effects underlies all computations.

An automated version of the collaboration process was implemented in MS Visual Basic. The optimization models were solved using the ILOG CPLEX 7.0 standard mathematical programming solver.

The structure of input parameters considered here is taken from Tempelmeier and

Summary and conclusions

In summary, a negotiation-based scheme for collaborative planning between two partners was laid out in this paper. It extends the simple coordination form of upstream planning by giving the collaboration partners an opportunity to modify suggested order/supply patterns in an iterative way. In doing so, mathematical programming planning models can be utilized. In particular, it has been shown how the same models as are applied to intra-domain master planning, can be used (in adapted versions)

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