用随机规划方法选择不确定条件下的木材供应合同

IF 1.1 4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Alireza Rahimi, M. Rönnqvist, L. Lebel, J. Audy
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引用次数: 1

摘要

森林工业的大部分费用与木材供应采购有关。有许多供应商参与其中,以有竞争力的价格获得木材供应合同是采购经理面临的一个持续挑战。一个主要的困难是采购面临各种采购风险,包括春季解冻的开始、合同违约或供应商不可靠。采购计划应预见到随机事件,并包括抵消其负面影响的措施。在计划追索行动时,必须考虑到数量的不确定性和木材价格的波动。依靠手工工具很难考虑到这个问题的所有方面。提出了一种支持采购计划制定的随机规划方法。在该模型中,包含了不同期限的固定合同、弹性合同和期权合同。从一个随机规划模型中提出的契约选择在可能的情况下产生平均最优性。所建立的两阶段随机规划模型决定了以总采购成本最小为目标的最优合同组合的选择。根据魁北克的一个案例研究,与确定性方法相比,使用随机规划平均节省4%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Selecting wood supply contracts under uncertainty using stochastic programming
Abstract A large portion of expenses in the forest industries is associated with wood supply procurement. Numerous suppliers are involved and securing wood supply contracts with competitive prices is a constant challenge for procurement managers. A major difficulty is the procurement exposure to various sourcing risks including the start of the spring thaw, contract breach, or unreliability of suppliers. A procurement plan should anticipate random events and include measures that counter their negative impact. Recourse actions must be planned by considering volume uncertainty and wood price fluctuations. Relying on manual tools is hardly capable of considering all aspects of this problem. A stochastic programming approach is proposed to support the development of a procurement plan. In this model, several types of contracts including fixed, flexible and option contracts with different durations are included. The proposed selection of contracts from a stochastic programming model yields average optimality in the presence of plausible scenarios. The developed two-stage stochastic programming model decides on the selection of the optimal portfolio of contracts to minimize total procurement costs. Based on a case study in Quebec, an average saving of 4% was shown by using stochastic programming compared to the deterministic approach.
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来源期刊
Infor
Infor 管理科学-计算机:信息系统
CiteScore
2.60
自引率
7.70%
发文量
16
审稿时长
>12 weeks
期刊介绍: INFOR: Information Systems and Operational Research is published and sponsored by the Canadian Operational Research Society. It provides its readers with papers on a powerful combination of subjects: Information Systems and Operational Research. The importance of combining IS and OR in one journal is that both aim to expand quantitative scientific approaches to management. With this integration, the theory, methodology, and practice of OR and IS are thoroughly examined. INFOR is available in print and online.
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