Author: Ali GuzelPublisher:
ISBN:
Category :
Languages : en
Pages : 268
Book Description
Optimal Commodity Procurement
Author: Ali GuzelCommodity Procurement with Operational and Financial Instruments
Author: Jan ArnoldPublisher: Springer Science & Business Media
ISBN: 3834986542
Category : Business & Economics
Languages : en
Pages : 159
Book Description
Jan Arnold integrates financial and operational aspects into a holistic approach to commodity procurement. He shows how to combine operational strategies considering just-in-time procurement, inventory holding and backlogging with financial strategies considering derivative instruments into an optimal procurement plan under volatile procurement prices.
Implementing Purchasing and Supply Chain Management
Author: Nancy NicosiaPublisher: Rand Corporation
ISBN: 0833039857
Category : Business & Economics
Languages : en
Pages : 142
Book Description
The U.S. Air Force plans to improve procurement through the implementation of additional purchasing and supply chain management practices. To emulate the success of commercial enterprises, the Air Force is establishing commodity councils to develop proactive, enterprise-wide strategies for purchasing key Air Force goods and services. This monograph helps the commodity councils approach the market research task. This monograph is organized around the process for conducting market research. It begins with background information, proceeds through the how-to steps for conducting market research, and ends with recommendations for next steps. The authors highlight lessons learned from both a literature review and from interviews with personnel at leading commercial enterprises.
Essays in optimization of commodity procurement, processing and trade operations
Author: Sripad Krishnaji DevalkarPublisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Industrial Engineering, Management Science and Applications 2015
Author: Mitsuo GenPublisher: Springer
ISBN: 3662472007
Category : Business & Economics
Languages : en
Pages : 1085
Book Description
This volume provides a complete record of presentations made at Industrial Engineering, Management Science and Applications 2015 (ICIMSA 2015), and provides the reader with a snapshot of current knowledge and state-of-the-art results in industrial engineering, management science and applications. The goal of ICIMSA is to provide an excellent international forum for researchers and practitioners from both academia and industry to share cutting-edge developments in the field and to exchange and distribute the latest research and theories from the international community. The conference is held every year, making it an ideal platform for people to share their views and experiences in industrial engineering, management science and applications related fields.
Integrating Commodity Futures in Procurement Planning and Contract Design with Demand Forecast Update
Author: Qiang LiPublisher:
ISBN: 9781361033739
Category :
Languages : en
Pages :
Book Description
This dissertation, "Integrating Commodity Futures in Procurement Planning and Contract Design With Demand Forecast Update" by Qiang, Li, 李強, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: This study aims at investigating the benefits of integrating commodity futures contracts in devising commodity procurement policies as well as the design of supply contracts. To achieve this, a two-tier decentralised supply chain with uncoordinated risk transfer behaviours is studied. Specifically, the supply chain consists of a risk-neutral manufacturer (he) and a risk-averse retailer (she), where both players maximise their own objective functions by utilising the demand forecast update over the planning horizon. The mean-variance utility is employed to capture the retailer''s risk aversion behaviour. For the first objective, this study considers a commodity procurement problem for the risk-neutral manufacturer. It shows that partially procuring in the forward market is potentially beneficial because the logistics costs tend to be larger for tighter delivery schedule and vice versa. Existing literature has studied the value of forward procurement. This study further explores the value of the dynamic adjustment in the forward (futures) market in response to the demand information update. Specifically, when the joint distribution of demand and new information is a bivariate normal distribution, the optimal procurement policy is characterized analytically. The second objective is studied within the supply chain setting, where the manufacturer is assumed to be the Stackelberg leader. Recently, various financial hedging strategies have been developed to mitigate the price risks for firms which directly procure commodities for their operations. However, few, if any, studies have addressed the integration of financial hedging with supply contract design so that the risk exposure faced by the downstream player in the supply chain could be partially hedged. Although the downstream retailer does not procure any commodity directly, she may suffer from the commodity price volatility propagated from the upstream manufacturer. By formulating the problem as a dynamic program, a flexible contract with time-consistent closed-form financial hedging policy is derived. Numerical experiments are carried out to demonstrate the benefits gained by integrating the commodity futures contract with supply chain decision making. In the implementation, the short-term/long-term model developed by Schwartz and Smith is adopted to describe the stochastic behaviour of the price. Moreover, to preclude any risk-free arbitrage opportunity, the risk-neutral version of the model is employed. To take full advantage of the historical commodity price data, the smoother-based approach, rather than filter-based approach, is adopted to estimate the latent parameters of the stochastic price processes. For the manufacturer, it is shown that the value of the futures market is significant in the presence of logistics cost. Moreover, extra value could be obtained by adjusting the position in futures contracts in response to the newly observed information. For the decentralised supply chain, compared with the wholesale price contract, it is shown that the proposed flexible contract could improve the performance of the supply chain by leading to higher payoffs for both firms. Furthermore, the results show that flexible contract with financial hedging is effective on mitigating the commodity price risk exposure transferred from the manufacturer to the retailer when measured by standard deviation (SD), value-a
Optimal Procurement and Inventory Control in Volatile Commodity Markets
Author: Christian MandlLong-Term Commodity Procurement Risk Management Using Futures Contracts
Author: Li ShiPublisher: Open Dissertation Press
ISBN: 9781361310021
Category :
Languages : en
Pages :
Book Description
This dissertation, "Long-term Commodity Procurement Risk Management Using Futures Contracts: a Dynamic Stack-and-roll Approach" by Li, Shi, 时莉, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: The procurement of commodity materials for production is an important issue in supply chain management. Effective procurement should consider both uncertain customer demand and fluctuating commodity price which, when act together, give rise to the procurement risk. To protect the bottom line, a manufacturer has to plan its procurement activities with special attention given to such procurement risk. Existing research has studied the use of exchange market-traded commodities in mitigating procurement risk. This study addresses the case of a manufacturer with long-term procurement commitments who wishes to hedge against the risk exposure by using long-dated futures contracts. In the commodities markets, however, long-dated futures are often illiquid or even unavailable, thus making the hedge ineffective. Alternatively, in a stack-and-roll hedge, the hedging positions are rolled forward in actively traded short-dated futures contracts of equal maturity until the procurement is executed. This in effect replicates the long-term futures contract in performing a hedge. This study therefore aims at developing a dynamic stack-and-roll approach that can effectively manage the long maturity procurement risk. The proposed dynamic stack-and-roll approach is inherently a discrete-time hedging strategy that divides the procurement planning horizon into multiple decision stages. The nearby futures are adopted as the short-dated futures as they are typically liquid. The hedging positions are adjusted periodically in response to the commodity price behaviour and updated information about the forward customer demand. For a manufacturer who wishes to mitigate the procurement risk as well as maximise the terminal revenue after the procurement, the mean-variance objective function is employed to model the manufacturer's risk aversion behaviour. Then, a dynamic program formulation of the approach is presented for determining a closed-form expression of the optimal hedging positions. Notice that the hedging policy is a time-consistent mean-variance policy in discrete-time, in contrast to the existing discrete hedging approaches that employ minimum-variance policies. In this study, the commodity prices are modelled by a fractal nonlinear regression process that employs a recurrent wavelet neural network as the nonlinear function. The purpose of this arrangement is to incorporate the fractal properties discovered in commodity prices series. In the wavelet transform domain, fractal self-similarity and self-affinity information of the price series over a certain time scale can be extracted. The Extended Kalman Filter (EKF) algorithm is applied to train the neural network for its lower training error comparing with classical gradient descent algorithms. Monthly returns and volatility of commodity prices are estimated by daily returns data in order to increase the estimation accuracy and facilitate effective hedging. The demand information is updated stage by stage using Bayesian inference. The updating process are defined and adapted to a filtration, which can be regarded as the information received at the beginning of each decision stage. Numerical experiments are carried out to evaluate the performance of the proposed stack-and-roll approach. The results show that the proposed approach robustly outperforms other hedging strategies that employ minimum-variance or nai
Commodity Procurement
Author: Integrated Optimization of Procurement, Processing and Trade of Commodities in a Network Environment
Author: Sripad K. DevalkarPublisher:
ISBN:
Category :
Languages : en
Pages : 49
Book Description
We consider the integrated optimization problem of procurement, processing and trade of commodities over a network in a multiperiod setting. Motivated by the operations of a prominent commodity processing firm, we model a firm that operates a star network with multiple locations at which it can procure an input commodity and has processing capacity at a central location to convert the input into a processed commodity. The processed commodity is sold using forward contracts, while the input itself can be traded at the end of the horizon. We show that the single-node version of this problem can be solved optimally when the procurement cost for the input is piecewise linear and convex, and derive closed form expressions for the marginal value of input and output inventory. However, these marginal values are hard to compute because of high dimensionality of the state space and we develop an efficient heuristic to compute approximate marginal values. We also show that the star network problem can be approximated as an equivalent single node problem and propose heuristics for solving the network problem. We conduct numerical studies to evaluate the performance of both the single node and network heuristics. We find that the single node heuristics are near-optimal, capturing close to 90% of the value of an upper bound on the optimal expected profits. Approximating the star network by a single node is effective, with the gap between the heuristic and upper bound ranging from 7% to 14% for longer planning horizons.