1,453 research outputs found

    Periodic review base-stock replenishment policy with endogenous lead times.

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    In this paper, we consider a two stage supply chain where the retailer's inventory is controlled by the periodic review, base-stock level (R,S) replenishment policy and the replenishment lead times are endogenously generated by the manufacturer's production system with finite capacity. We extend the work of Benjaafar and Kim (2004) who study the effect of demand variability in a continuously reviewed base-stock policy with single unit demands. In our analysis, we allow for demand in batches of variable size, which is a common setting in supply chains. A procedure is developed using matrix analytic methods to provide an exact calculation of the lead time distribution, which enables the computation of the distribution of lead time demand and consequently the safety stock in an exact way instead of using approximations. Treating the lead time as an endogenous stochastic variable has a substantial impact on safety stock. We numerically show that the exogenous lead time assumption may dramatically degrade customer service.Production/inventory systems; Base-stock replenishment policy; endogenous lead times; Safety stock; Phase-type distribution; Matrix-analytical methods;

    A smoothing replenishment policy with endogenous lead times.

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    We consider a two echelon supply chain consisting of a single retailer and a single manufacturer. Inventory control policies at the retailer level often transmit customer demand variability to the manufacturer, sometimes even in an amplified form (known as the bullwhip effect). When the manufacturer produces in a make-to-order fashion though, he prefers a smooth order pattern. But dampening the variability in orders inflates the retailer's safety stock due to the increased variance of the retailers inventory levels. We can turn this issue of conflicting objectives into a win-win situation for both supply chain echelons when we treat the lead time as an endogenous variable. A less variable order pattern generates shorter and less variable (production/replenishment) lead times, introducing a compensating effect on the retailer's safety stock. We show that by including endogenous lead times, the order pattern can be smoothed to a considerable extent without increasing stock levels.Bullwhip effect; Demand; endogenous lead times; Fashion; Inventory; Inventory control; Markov processes; Order; Policy; Queueing; Research; Safety stock; Smoothing; Supply chain; Supply chain management; Time; Variability; Variance;

    Coordination and synchronization of material flows in supply chains: an analytical approach.

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    The coordination of joint material flows is a key element in supply chain management. Although analytical models for the coordination of materials are of great practical value, literature analyzing them remains scarce. This article contributes to this gap by studying a generic supply chain model. The supply chain is assumed to have a single production facility that is supplied by two independent suppliers. The field of combinatorics serves as a means to derive exact results for important performance measures, and the results suggest insights related to several supply chain management principles.Assembly; Synchronization; Coordination; Supply chain; Combinatorics;

    The influence of demand variability on the performance of a make-to-stock queue

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    Variability, in general, has a deteriorating effect on the performance of stochastic inventory systems. In particular, previous results indicate that demand variability causes a performance degradation in terms of inventory related costs when production capacity is unlimited. In order to investigate the effects of demand variability in capacitated production settings, we analyze a make-to-stock queue with general demand arrival times operated according to a basestock policy. We show that when demand inter-arrival distributions are ordered in a stochastic sense, increased arrival time variability indeed leads to an augmentation of optimal base-stock levels and to a corresponding increase in optimal inventory related costs. We quantify these effects through several numerical examplesproduction/inventory; make-to-stock; base-stock; stochastic comparisons; GI/M/1, POLICIES; COSTS; SYSTEMS; LEAD

    Finding optimal policies in the (S - 1, S ) lost sales inventory model with multiple demand classes

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    This paper examines the algorithms proposed in the literature forfinding good critical level policies in the (S-1,S) lost salesinventory model with multiple demand classes. Our main result isthat we establish guaranteed optimality for two of thesealgorithms. This result is extended to different resupplyassumptions, such as a single server queue. As a corollary, weprovide an alternative proof of the optimality of critical levelpolicies among the class of all policies.inventory;customer differentiation;multiple demand classes;rationing lost sales;stochastic dynamic programming

    The impact of replenishment rules with endogenous lead times on supply chain performance..

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    In dit proefschrift beperken we ons tot een basis supply chain met één klant en één producent. We bestuderen verschillende bestelpolit ieken van de klant, en meten de impact van deze bestelregels op de produ ctie van de producent. We modelleren het productieproces als een wachtli jn- of queueing model. Uit de analyse van dit productiemodel vinden we de levertijden, die op hun beurt gebruikt worden in het voorra admodel van de klant. De methodologie die hiervoor gebruikt wordt, is tw eevoudig. Enerzijds maken we gebruik van statistische technieken om de v oorraad te beheren en bestellingen te plaatsen. Anderzijds maken we gebr uik van wachtlijntheorie en Markov ketens om de doorlooptijden te bepale n. Eerst onderzoeken we een eenvoudige "chase sales" bestelpolit iek: de klant plaatst elke periode een bestelling die gelijk is aan de c onsumentenvraag. We ontwikkelen een efficiënte procedure om de impact va n deze bestelregel op de doorlooptijden te berekenen op basis van

    Operations research and computers

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