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Managing Shutdown Decisions in Merchant Commodity and Energy Production: A Social Commerce Perspective

机译:在商品和能源生产中管理关机决策:社会商务观点

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ibProblem definition : Merchant commodity and energy production assets operate in markets with volatile prices and exchange rates. Plant closures adversely affect societal entities beyond the specific plant being shut down, such as the parent company and the local community. Motivated by an aluminum producer, we study if mitigating these hard-to-assess broader impacts of a shutdown is financially viable using the plant’s operating flexibility. biAcademic/practical relevance : Our social commerce perspective toward managing shutdown decisions deviates from the commonly used asset value maximization objective in merchant operations. Identifying operating policies that delay or decrease the likelihood of a shutdown without incurring a significant asset value loss supports socially responsible plant shutdown decisions. biMethodology : We formulate a constrained Markov decision process to manage shutdown decisions and limit the probability of future plant closures. We provide theoretical support for approximating this intractable model using unconstrained stochastic dynamic programs with modified shutdown costs and explore two classes of operating policies. Our first policy leverages anticipated regret theory, and the second policy generalizes, using machine learning, production-margin heuristics used in practice. We compute the former and latter policies using a least squares Monte Carlo method and combining this method with binary classification, respectively. biResults : Anticipated-regret policies possess desirable asymptotic properties absent in classification-based policies. On instances created using real data, anticipated-regret and classification-based policies outperform practice-based production-margin strategies. Significant reductions in shutdown probability and delays in plant closures are possible while incurring small asset value losses. biManagerial implications : A plant’s operating flexibility provides an effective lever to balance the social objective to reduce closures and the financial goal to maximize asset value. Adhering to both objectives requires combining short-term commitments with external stakeholders to avoid shutdown with longer-term internal efforts to reduce the probability of plant closures.
机译:问题定义:商品和能源生产资产在市场上以波动价格和汇率运作。植物封闭对特定植物被关闭的特定植物(如母公司和当地社区)产生不利影响社会实体。通过铝生产商的动机,我们研究如果减轻这些难以评估的更广泛的影响,则使用该工厂的经营灵活性来融资。 学术/实际相关性:我们的社会商务朝着管理关机决策的观点偏离了商业运营中的常用资产价值最大化目标。识别延迟或减少关闭的可能性的操作策略而不会产生重大资产价值损失,支持社会负责的工厂关闭决策。 方法:我们制定受限制的马尔可夫决策过程,以管理关机决策并限制未来植物封闭的可能性。我们提供了使用具有修改的关机成本的无约束随机动态程序近似这种难以应变模型的理论支持,并探索两类操作策略。我们的第一款政策利用预期遗憾的理论,第二个政策概括,使用在实践中使用的机器学习,生产 - 保证金启发式。我们使用最小二乘蒙特卡罗方法计算前者和后一种策略,并分别将这种方法与二进制分类相结合。 结果:预期 - 遗憾的政策具有基于分类的政策中缺席的理想的渐近性。在使用真实数据创建的实例上,预期遗憾和基于分类的策略优于基于练习的生产保证金策略。在发生小额资产价值损失的同时,可能会对植物闭合概率和延迟进行显着降低。 管理含义:工厂的操作灵活性为一个有效的杠杆提供了平衡社会目标,以减少关闭和财务目标,以最大限度地提高资产价值。遵守两个目标需要将与外部利益相关者的短期承诺相结合,以避免随着长期内部努力而关闭以减少植物封闭的可能性。

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