44,140 research outputs found
Buyback and return policies for a book publishing firm = Egy könyvkiadó vållalat visszavåsårlåsi stratégiåja
A dolgozat cĂ©lja egy vĂĄllalati gyakorlatbĂłl szĂĄrmazĂł eset elemzĂ©se. Egy könyvkiadĂłt tekintĂŒnk. A kiadĂł kapcsolatban van kis- Ă©s nagykereskedĆkkel, valamint a fogyasztĂłk egy csoportjĂĄval is vannak kapcsolatai. A könyvkiadĂłk projekt rendszerben mƱködnek. A kiadĂł azzal a problĂ©mĂĄval szembesĂŒl, hogy hogyan ossza el egy frissen kiadott Ă©s nyomtatott könyv pĂ©ldĂĄnyszĂĄmait a kis- Ă©s nagykereskedĆk között, valamint mekkora pĂ©ldĂĄnyszĂĄmot tĂĄroljon maga a fogyasztĂłk közvetlen kielĂ©gĂtĂ©sĂ©re. A kiadĂłrĂłl feltĂ©telezzĂŒk, hogy visszavĂĄsĂĄrlĂĄsi szerzĆdĂ©se van a kereskedĆkkel. A könyv irĂĄnti kereslet nem ismert, de becsĂŒlhetĆ. A kis- Ă©s nagykereskedĆk maximalizĂĄljĂĄk a nyeresĂ©gĂŒket. = The aim of the paper is to analyze a practical real world problem. A publishing house is given. The publishing firm has contacts to a number of wholesaler / retailer enterprises and direct contact to customers to satisfy the market demand. The book publishers work in a project industry. The publisher faces with the problem how to allocate the stocks of a given, newly published book to the wholesaler and retailer, and to hold some copies to satisfy the customers direct from the publisher. The publisher has a buyback option. The distribution of the demand is unknown, but it can be estimated. The wholesaler / retailer maximize the profits.
The problem can be modeled as a one-warehouse and N-retailer supply chain with not identical demand distribution. The model can be transformed in a game theory problem. It is assumed that the demand distribution follows a Poisson distribution
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Derivation of near-optimal pump schedules for water distribution by simulated annealing
The scheduling of pumps for clean water distribution is a partially discrete non-linear problem with many variables. The scheduling method described in this paper typically produces costs within 1% of a linear program-based solution, and can incorporate realistic non-linear costs that may be hard to incorporate in linear programming formulations. These costs include pump switching and maximum demand charges. A simplified model is derived from a standard hydraulic simulator. An initial schedule is produced by a descent method. Two-stage simulated annealing then produces solutions in a few minutes. Iterative recalibration ensures that the solution agrees closely with the results from a full hydraulic simulation
Firm-Network Characteristics and Economic Robustness to Natural Disasters
This article proposes a theoretical framework to investigate economic robustness to exogenous shocks such as natural disasters. It is based on a dynamic model that represents a regional economy as a network of production units through the disaggregation of sectorscale Input-Output tables. Results suggest that disaster-related output losses depend on direct losses heterogeneity and on the economic network structure. Two aggregate indexes, concentration and clustering, appear as important drivers of economic robustness, offering opportunities for robustness-enhancing strategies. Modern industrial organization seems to reduce short-term robustness in a trade-off against higher efficiency in normal times.Natural disasters, Economic impacts, Economic Network.
Investment and Pricing with Spectrum Uncertainty: A Cognitive Operator's Perspective
This paper studies the optimal investment and pricing decisions of a
cognitive mobile virtual network operator (C-MVNO) under spectrum supply
uncertainty. Compared with a traditional MVNO who often leases spectrum via
long-term contracts, a C-MVNO can acquire spectrum dynamically in short-term by
both sensing the empty "spectrum holes" of licensed bands and dynamically
leasing from the spectrum owner. As a result, a C-MVNO can make flexible
investment and pricing decisions to match the current demands of the secondary
unlicensed users. Compared to dynamic spectrum leasing, spectrum sensing is
typically cheaper, but the obtained useful spectrum amount is random due to
primary licensed users' stochastic traffic. The C-MVNO needs to determine the
optimal amounts of spectrum sensing and leasing by evaluating the trade off
between cost and uncertainty. The C-MVNO also needs to determine the optimal
price to sell the spectrum to the secondary unlicensed users, taking into
account wireless heterogeneity of users such as different maximum transmission
power levels and channel gains. We model and analyze the interactions between
the C-MVNO and secondary unlicensed users as a Stackelberg game. We show
several interesting properties of the network equilibrium, including threshold
structures of the optimal investment and pricing decisions, the independence of
the optimal price on users' wireless characteristics, and guaranteed fair and
predictable QoS among users. We prove that these properties hold for general
SNR regime and general continuous distributions of sensing uncertainty. We show
that spectrum sensing can significantly improve the C-MVNO's expected profit
and users' payoffs.Comment: A shorter version appears in IEEE INFOCOM 2010. This version has been
submitted to IEEE Transactions on Mobile Computin
Multilevel Pricing Schemes in a Deregulated Wireless Network Market
Typically the cost of a product, a good or a service has many components.
Those components come from different complex steps in the supply chain of the
product from sourcing to distribution. This economic point of view also takes
place in the determination of goods and services in wireless networks. Indeed,
before transmitting customer data, a network operator has to lease some
frequency range from a spectrum owner and also has to establish agreements with
electricity suppliers. The goal of this paper is to compare two pricing
schemes, namely a power-based and a flat rate, and give a possible explanation
why flat rate pricing schemes are more common than power based pricing ones in
a deregulated wireless market. We suggest a hierarchical game-theoretical model
of a three level supply chain: the end users, the service provider and the
spectrum owner. The end users intend to transmit data on a wireless network.
The amount of traffic sent by the end users depends on the available frequency
bandwidth as well as the price they have to pay for their transmission. A
natural question arises for the service provider: how to design an efficient
pricing scheme in order to maximize his profit. Moreover he has to take into
account the lease charge he has to pay to the spectrum owner and how many
frequency bandwidth to rent. The spectrum owner itself also looks for
maximizing its profit and has to determine the lease price to the service
provider. The equilibrium at each level of our supply chain model are
established and several properties are investigated. In particular, in the case
of a power-based pricing scheme, the service provider and the spectrum owner
tend to share the gross provider profit. Whereas, considering the flat rate
pricing scheme, if the end users are going to exploit the network intensively,
then the tariffs of the suppliers (spectrum owner and service provider)
explode.Comment: This is the last draft version of the paper. Revised version of the
paper accepted by ValueTools 2013 can be found in Proceedings of the 7th
International Conference on Performance Evaluation Methodologies and Tools
(ValueTools '13), December 10-12, 2013, Turin, Ital
Quantitative analysis of multi-periodic supply chain contracts with options via stochastic programming
We propose a stochastic programming approach for quantitative analysis of supply contracts, involving flexibility, between a buyer and a supplier, in a supply chain framework. Specifically, we consider the case of multi-periodic contracts in the face of correlated demands. To design such contracts, one has to estimate the savings or costs induced for both parties, as well as the optimal orders and commitments. We show how to model the stochastic process of the demand and the decision problem for both parties using the algebraic modeling language AMPL. The resulting linear programs are solved with a commercial linear programming solver; we compute the economic performance of these contracts, giving evidence that this methodology allows to gain insight into realistic problems.stochastic programming; supply contract; linear programming; modeling software; decision tree
Measuring the variability in supply chains with the peakedness
This paper introduces a novel way to measure the variability of order flows in supply chains, the peakedness. The peakedness can be used to measure the variability assuming the order flow is a general point pro- cess. We show basic properties of the peakedness, and demonstrate its computation from real-time continuous demand processes, and cumulative demand collected at fixed time intervals as well. We also show that the peakedness can be used to characterize demand, forecast, and inventory variables, to effectively manage the variability. Our results hold for both single stage and multistage inventory systems, and can further be extended to a tree-structured supply chain with a single supplier and multiple retailers. Furthermore, the peakedness can be applied to study traditional inventory problems such as quantifying bullwhip effects and determining safety stock levels. Finally, a numerical study based on real life Belgian supermarket data verifies the effectiveness of the peakedness for measuring the order flow variability, as well as estimating the bullwhip effects.variability, peakedness, supply chain
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