The impact of material coordination concepts on planning stability in supply chains

Donselaar, van Kh Karel; Nieuwenhof, van den J; Visschers, Jwch Jeremy

doi:10.1016/s0925-5273(00)00033-5

Cited by 48 publications

(18 citation statements)

References 12 publications

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“…The essence of LRP is the fact that demand information from the final customer is transferred directly to each of the stages in supply chain, so that the final information of demand is not distorted. Donselaar et al (2000) compare the performance of MRP and LRP systems in a stochastic environment, performance being estimated by the service level, inventory levels and the planning nervousness. The results of the experiment show that both MRP and LRP concepts of planning possess important characteristics for stochastic environments, but development of new models that combine these characteristics is called for.…”

Section: Materials Requirement Planning (Mrp)mentioning

confidence: 99%

Models for production planning under uncertainty: A review

Mula

García-Sabater

et al. 2006

International Journal of Production Economics

535

252

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The consideration of uncertainty in manufacturing systems supposes a great advance. Models for production planning which do not recognize the uncertainty can be expected to generate inferior planning decisions as compared to models that explicitly account for the uncertainty. This paper reviews some of the existing literature of production planning under uncertainty. The research objective is to provide the reader with a starting point about uncertainty modelling in production planning problems aimed at production management researchers. The literature review that we compiled consists of 87 citations from 1983 to 2004. A classification scheme for models for production planning under uncertainty is defined. r

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Section: Materials Requirement Planning (Mrp)mentioning

confidence: 99%

Models for production planning under uncertainty: A review

Mula

García-Sabater

et al. 2006

International Journal of Production Economics

535

252

View full text Add to dashboard Cite

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“…We have used the symbol <,>to represent a symmetric triangular fuzzy number following the notation proposed by Inuiguchi et al [15]. It is not really an interval, represented by the symbol [, ], with a minimum and a maximum value of the tolerance interval.…”

Section: Programmed Receptions Of the Product I On Period T [Z1 Z1 +mentioning

confidence: 99%

Fuzzy Material Requirements Planning

Feili¹,

Moghaddam²,

Zahmatkesh³

2010

J. Math. Computer Sci.

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Abstract:Various modeling techniques based on possibility distribution function has been applied successfully in a wide range of issues related to production planning. However, the possibility distribution function derived from the records recorded in the organization are not always available or changes in production environment may cause a variety of changes and volatilities in model and make it unreliable; changes such as: market demand, changes in types of production costs, capacity, resources, and administrative constraints. In this study fuzzy sets theory has been combined with material requirements planning (MRP). It is noteworthy that material requirements planning (MRP) is one of the most commonly used subdivision of production planning that combining it with fuzzy theory can be applied to develop decision making systems and make them more efficient. In addition, the uncertainties of industrial environments can be exerted properly into the production decision-making.

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“…The next rule proposed by Donselaar et al (2000) is summarized as follows: At time t we check for each period t + x (x = 0, 1, 2, …,T-1):…”

Section: Deterministicmentioning

confidence: 99%