An analytic approach to production capacity allocation and supply chain design

Korpela, Jukka; Kyläheiko, Kalevi; Lehmusvaara, Antti; Tuominen, Markku

doi:10.1016/s0925-5273(01)00101-3

Cited by 94 publications

(47 citation statements)

References 13 publications

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“…Keskinocak et al (2001) studied several online and oine algorithms for quoting various lead times to dierent customer classes where revenues obtained from the customers are sensitive to the lead time. Korpela et al (2002) emphasized that customers are not equally important for a company and, therefore, a supplier should select valuable customers in order to allocate its resources optimally. They proposed a model for developing a sales plan where the limited production capacity was allocated to the customers regarding their strategic importance.…”

Section: Customer Segmentationmentioning

confidence: 99%

An agent-based model to support negotiation-based order acceptance in a multi-plant enterprise

Mobini

Behdani

Lukszo

et al. 2011

2011 IEEE International Conference on Systems, Man, and Cybernetics

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SummaryOrder acceptance (OA) has a large inuence on the performance of an enterprise. On the one hand, always accepting an order when capacity is available may restrict the system to accept more protable orders in the future. On the other hand, rejecting too many orders leads to low capacity utilization and also has repercussions for future customer relations. In addition, accepting too many orders leads to an over-loaded production environment, where lead times increase and orders are delivered late. Most of these aspects of order acceptance decision-making can be handled by having proper negotiations with customers on order terms. However, this is a complex problem primarily because there are dierent actors who have various (conicting) interests, needs and objectives. Accordingly, to provide insight for the decision makers in the rms in order to develop proper strategies for order acceptance, developing appropriate models seems necessary.The objective in this research is to improve the order acceptance performance of a make-to-order multi-plant enterprise (MPE) by incorporating buyer-seller negotiations in its OA procedure with the main research question of How can the buyer-seller negotiation process contribute to the improvement of order acceptance performance in the multi-plant enterprise?For this purpose, we have developed an agent-based model to support order acceptance decisions in a multi-plant enterprise particularly using dierent negotiation settings.The research starts with literature review on order acceptance in general and negotiation in particular. A gap is identied in the OA literature: the major perspectives on the OA procedure rest on the underlying assumption that order terms are already determined which is not always tenable. In reality, order terms are usually specied by negotiation between the buyer and the seller and they are not predetermined. A negotiation-based order acceptance approach is consequently suggested in order to consider the whole activities in a negotiation process with three phases. The proposed process involves the initiation conditions for negotiation (pre-negotiation phase), the main interaction (negotiation phase) and the consequences of negotiation on the future decisions of the involved actors (post-negotiation phase). This negotiation process is a part of more general negotiation framework which is then extended into a negotiation ontology. The ontology introduces the main concepts and their relations in a negotiation problem. Next, the conceptualization of the order negotiation process in OA and the negotiation ontology are used in developing an agent-based model for buyer-seller negotiations in a case of multi-plant enterprise. The general assumptions and settings for model development are taken from a model have been presented by Behdani et al. (2010) for a lube oil multi-plant case study motivated by a real supply chain.In this research, the previous model is extended by incorporating negotiation between the ii enterprise and its customers on order terms. Final...

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Section: Customer Segmentationmentioning

confidence: 99%

An agent-based model to support negotiation-based order acceptance in a multi-plant enterprise

Mobini

Behdani

Lukszo

et al. 2011

2011 IEEE International Conference on Systems, Man, and Cybernetics

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“…In other words, pure analytical approach is not powerful enough to solve SC problems. Korpela et al [59] developed a framework for analytical approach to allocate production capacity in SC. The framework based on analytical hierarchy process (AHP) and mixed integer programming (MIP).…”

Section: Production/order Distribution Production Planning and Schedmentioning

confidence: 99%

The future trend on system-wide modelling in supply chain studies

Chan

2004

Int J Adv Manuf Technol

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Although supply chain (SC) has gained increasing attention in the last decade and numerous SC problems have been identified and solved, there is a lack of systematic approach to solve SC problems at a system level. SC can be viewed as a network of organisations including, but not restricted to, the suppliers (source of raw materials), manufacturers, distributors, retailers, and end customers. Each entity is able to process different tasks individually in order to satisfy the global goal of the network, which is usually the total cost or lead time of a set of products. If only inter-entity problems are solved, like inventory level, production planning, etc., the performance of the whole system is not guaranteed to be acceptable. The main objective of this paper is to review contemporary SC problems and the methodologies in solving them, and to suggest future research direction for solving supply chains problems. From the analysis of the review, it can be concluded that there is limited research to solve SC problems from a "system" point of view. In this connection, future direction in solving system-wide SC, and the potential difficulties, are discussed. This allows readers to gain insights in the future research direction in the area of supply chain management.

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“…profitability, customer credibility and delivery date. Korpela et al (2002) used AHP process to prioritize orders according to the strategic importance of customer to an organization. Their objective was to prioritize those customers who were more important to the company when faced with shortage of production capacity.…”

Section: Introductionmentioning

confidence: 99%

An order acceptance using FAHP and TOPSIS methods: A case study of Iranian vehicle belt production industry

Parsaei¹,

Keramati²,

Zorriassatine³

et al. 2012

ijiec

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Decisions related to acceptance or rejection of orders play an important role in companies engaged in make-to-order production. The incoming orders have a specific delivery date by which the customer expects the due date to be met and the order delivered. In some cases the level of input orders exceeds beyond the existing capacity. In such situations the main concern is to decide which orders must be accepted and which ones rejected taking into account the available production capacity. This paper prioritises the input orders according to a comprehensive and systematic multi criteria decision making (MCDM) model. It then proceeds with making decisions to either accept or reject orders according to the calculated prioritises and production constraints. Ultimately the optimum list of orders for acceptance is determined. The proposed model is a combination of two techniques of Fuzzy Analytical Hierarchy Process (FAHP) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). In this model FAHP is used to determine the weights of criteria and TOPSIS is used for prioritizing the orders. Finally the proposed model is tested for its efficiency by application to a real case.

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An analytic approach to production capacity allocation and supply chain design

Cited by 94 publications

References 13 publications

An agent-based model to support negotiation-based order acceptance in a multi-plant enterprise

An agent-based model to support negotiation-based order acceptance in a multi-plant enterprise

The future trend on system-wide modelling in supply chain studies

An order acceptance using FAHP and TOPSIS methods: A case study of Iranian vehicle belt production industry

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