Omega-international Journal of Management Science最新文献_第7页

A novel hybrid optimization approach for cost-efficient pump scheduling in water supply systems 一种新的混合优化方法用于供水系统中水泵的经济高效调度

IF 6.7 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-01-01 Epub Date: 2025-06-17 DOI: 10.1016/j.omega.2025.103378

Marlene Brás , Ana Moura , António Andrade-Campos

Optimizing pump scheduling in water supply systems (WSS) is crucial for reducing energy costs and improving operational efficiency. This paper presents a detailed analysis of the duty-cycles formulation, a mathematical model of the Pump Scheduling Problem (PSP) that enables a flexible pump operation over the total time horizon. Combined with the Sequential Least Squares Quadratic Programming (SLSQP) gradient-based method, this approach has shown superior computational efficiency and cost savings in previous studies. However, problems, such as a multiplicity of optimal solutions, local minima, and size scalability, were encountered. In addition, this paper introduces a new hybrid method, the Smart Dynamic Local Search (Smart-DLS), designed to overcome the identified challenges. This new approach integrates a deterministic local search with an intelligent shaking process to explore the solution space and avoid local optima efficiently. The framework’s performance is demonstrated through three case studies, including a real-world WSS, achieving significant cost reductions and showing strong generalizability across diverse scenarios. For the AnyTown network, it reaches more than 5%, and for the real network, 3% of cost reduction.

在供水系统中，优化水泵调度对降低能源成本和提高运行效率至关重要。本文详细分析了占空比公式，这是一个泵调度问题（PSP）的数学模型，可以在整个时间范围内实现灵活的泵运行。该方法与基于序列最小二乘二次规划（SLSQP）梯度的方法相结合，在前人的研究中显示出优越的计算效率和成本节约。然而，遇到了最优解的多重性、局部最小值和大小可伸缩性等问题。此外，本文还介绍了一种新的混合方法——智能动态局部搜索（Smart- dls），旨在克服上述挑战。该方法将确定性局部搜索与智能抖动过程相结合，有效地探索解空间并避免局部最优。该框架的性能通过三个案例研究（包括一个现实世界的WSS）进行了演示，实现了显著的成本降低，并在不同的场景中显示出强大的通用性。对于AnyTown网络，降低了5%以上，对于真实网络，降低了3%的成本。

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引用次数: 0

Robust de novo programming under different uncertainty sets and its application to the renewable energy sector 不同不确定集下的鲁棒从头规划及其在可再生能源领域的应用

IF 6.7 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-01-01 Epub Date: 2025-07-16 DOI: 10.1016/j.omega.2025.103389

Noureddine Kouaissah

This paper proposes robust models of de novo programming (R-DNP) using cardinality-constrained robustness with interval-based, ellipsoidal, and norm-based uncertainty sets. R-DNP has not been researched or explored, and we aim to fill this gap in the literature. In particular, we develop the robust counterpart of the weighted DNP (W-DNP), Chebyshev DNP (C-DNP), and extended DNP (E-DNP) models to incorporate different uncertainty sets and decision-makers’ preferences. Methodologically, the proposed approach extends the conventional DNP model to solve uncertain coefficients for each decision variable on the left-hand side of each objective function and on the total budget, overcoming the limitations of the current multicriteria solution procedure of the DNP approach. The proposed methods provide decision-makers with more flexibility to express their level of conservatism and preferences by setting priority weights and aspiration levels. The proposed method’s usefulness over the standard DNP is demonstrated by providing an illustrative example. Moreover, we validate the proposed formulations for solving real-world problems through a hypothetical application: optimizing onshore wind farm locations in Morocco. The work’s results confirm the validity of the proposed methodologies, showing that they can assist decision-makers in determining the optimal system design for sustainable electricity generation under uncertain conditions.

本文提出了基于区间、椭球和范数的不确定性集的基于基数约束的鲁棒性的从头规划（R-DNP）鲁棒模型。R-DNP尚未被研究或探索，我们的目标是填补这一空白的文献。特别是，我们开发了加权DNP (W-DNP), Chebyshev DNP （C-DNP）和扩展DNP （E-DNP）模型的鲁棒对应模型，以纳入不同的不确定性集和决策者的偏好。在方法上，该方法扩展了传统的DNP模型，在每个目标函数的左侧和总预算上求解每个决策变量的不确定系数，克服了当前DNP方法多准则求解过程的局限性。所提出的方法通过设置优先级权重和期望水平，为决策者提供了更大的灵活性来表达他们的保守性和偏好水平。通过一个实例证明了该方法相对于标准DNP的有效性。此外，我们通过一个假设的应用验证了提出的解决现实问题的公式：优化摩洛哥的陆上风电场位置。工作结果证实了所提出方法的有效性，表明它们可以帮助决策者在不确定条件下确定可持续发电的最佳系统设计。

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引用次数: 0

Rational versus presumptive decisions in a decentralized co-production system: Solutions and applications 分散合作生产系统中的理性决策与假定决策：解决方案和应用程序

IF 7.2 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-01-01 Epub Date: 2025-09-24 DOI: 10.1016/j.omega.2025.103412

Zhixuan Cai , Tianhu Deng , Christopher S. Tang

Recent research has examined the decentralized decisions of two independent parties when the system output is co-produced, i.e., the output depends on the efforts exerted by both parties. In this paper, we present a general modeling framework to reexamine the robustness of the results obtained from this stream of research. To model the decision-making process in a decentralized co-production system, we use the Constant Elasticity of Substitution (CES) function to model the output co-produced from the two parties and consider both simultaneous-move and sequential-move games. We also compare the equilibrium efforts exerted by rational firms and the optimal efforts exerted by presumptive firms. Here, each rational firm makes decisions by anticipating the other firm’s rational decision, whereas each presumptive firm makes decisions based on a prior belief about the other firm’s decision. We show that both simultaneous-move and sequential-move games yield similar structural results. First, the effort exerted by each rational (or presumptive) firm increases with the firm’s “returns on effort investment”. Second, while the efforts exerted by presumptive firms are not in equilibrium, we find that these off-equilibrium efforts can result in higher payoffs than the efforts exerted by rational firms when the prior beliefs are sufficiently high and effort cost factors are sufficiently low. We also apply these results to reexamine some key findings obtained in the recent literature whose co-production model can be viewed as special cases of the CES output function. We find that the existing results based on the special case may not hold under the general CES functions. Hence, our general model and results provide new insights. Finally, we demonstrate how our general model can be applied to examine other settings arising from product development and capacity planning decisions involving two independent parties with self-interests.

最近的研究考察了当系统产出是共同生产时，即产出取决于双方的努力时，两个独立的参与方的分散决策。在本文中，我们提出了一个通用的建模框架，以重新检查从这一研究流中获得的结果的鲁棒性。为了对分散合作生产系统中的决策过程进行建模，我们使用恒定替代弹性（CES）函数对双方共同生产的输出进行建模，并考虑同时移动和顺序移动博弈。我们还比较了理性企业的均衡努力和假设企业的最优努力。在这里，每个理性企业通过预测其他企业的理性决策来做出决策，而每个假定企业基于对其他企业决策的先验信念来做出决策。我们表明，同时移动和顺序移动游戏产生相似的结构结果。首先，每个理性（或假定）企业所付出的努力随着企业“努力投资回报”的增加而增加。第二，虽然假设企业的努力不是均衡的，但我们发现，当先验信念足够高而努力成本因素足够低时，这些非均衡的努力比理性企业的努力产生更高的回报。我们还应用这些结果来重新审视最近文献中获得的一些关键发现，这些文献中的合作生产模型可以被视为CES输出函数的特殊情况。我们发现，在一般的CES函数下，基于特殊情况的现有结果可能不成立。因此，我们的一般模型和结果提供了新的见解。最后，我们演示了如何将我们的一般模型应用于检查涉及两个具有自身利益的独立方的产品开发和能力规划决策所产生的其他设置。

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引用次数: 0

Strategic pricing and advertising decisions under competition with long-term advertising effects 长期广告效应下的战略定价与广告决策

IF 6.7 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-01-01 Epub Date: 2025-05-29 DOI: 10.1016/j.omega.2025.103360

Yuhong He , Jianghua Wu , Xiao Xiao

This study examines how negative long-term advertising effects influence startups’ strategic choices between myopic and far-sighted approaches in competitive markets. Using a two-period game model, it analyzes how firms balance the short-term benefits of advertising with its potential long-term drawbacks when making pricing and promotional decisions. The analysis shows that when advertising has positive long-term effects, far-sighted strategies are theoretically optimal regardless of the timing of advertising decisions. In practice, however, startups may struggle to sustain such approaches, as early-stage losses can create financial pressure that pushes them toward short-term survival strategies. When long-term advertising effects are negative, the optimal strategy becomes more sensitive to market conditions. The model shows that in markets with low product substitutability, far-sighted strategies continue to deliver better outcomes. As products become more similar, myopic strategies become more attractive—especially when the negative long-term effects are relatively mild. Furthermore, when the short-term impact of advertising is particularly strong, a myopic strategy can outperform a far-sighted one, even if long-term consequences are unfavorable. Under certain conditions, both firms choosing far-sighted strategies may also lead to a Prisoner’s Dilemma, where mutual restraint results in lower overall profits. These findings highlight the complex trade-offs startups face between short-term gains and long-term viability. Startups must weigh immediate advertising returns against potential long-term costs and develop pricing and advertising strategies that reflect both market dynamics and sustainable growth objectives.

本研究考察了在竞争市场中，负面的长期广告效应如何影响创业公司在短视和远见之间的战略选择。使用一个两期博弈模型，它分析了公司在定价和促销决策时如何平衡广告的短期利益和潜在的长期弊端。分析表明，当广告具有积极的长期效应时，无论广告决策的时机如何，有远见的策略在理论上都是最优的。然而，在实践中，创业公司可能很难维持这种方法，因为早期的损失可能会产生财务压力，迫使他们采取短期生存策略。当长期广告效应为负时，最优策略对市场条件更加敏感。该模型表明，在产品可替代性较低的市场中，有远见的策略继续带来更好的结果。随着产品变得越来越相似，短视策略变得更有吸引力——尤其是当长期负面影响相对温和的时候。此外，当广告的短期影响特别强烈时，短视的策略可以胜过有远见的策略，即使长期后果是不利的。在一定条件下，两家公司选择高瞻远瞩的战略也可能导致囚徒困境，即相互约束导致整体利润降低。这些发现凸显了创业公司在短期收益和长期生存能力之间所面临的复杂权衡。初创公司必须权衡即时广告回报和潜在的长期成本，并制定定价和广告策略，以反映市场动态和可持续增长目标。

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引用次数: 0

Order quantity optimization model for perishable products under continuous review (Q, r) inventory policy with stochastic demand and positive lead time 随机需求和正交货期的连续评审（Q, r）库存策略下易腐产品订单数量优化模型

IF 6.7 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-01-01 Epub Date: 2025-06-24 DOI: 10.1016/j.omega.2025.103392

Pavee Siriruk, Apicha Kotekangpoo

Expired perishable products impose costs on businesses, making effective inventory control essential for reducing wastage and enhancing profitability. This research proposes a mathematical model for determining the optimal order quantity of perishable products under a continuous review

(Q, r)

inventory policy, with a fixed lifetime, stochastic demand, and a positive lead time. Unlike conventional models, the proposed approach incorporates outdating costs into the total expected cost calculation. Due to the model’s computational complexity, the evolution strategy (μ + λ) optimization algorithm is employed to optimize the order quantity (

Q^{*}

) with minimum total expected cost. Numerical experiments are carried out using a case study of a hospital blood bank in Thailand. Sensitivity analysis is conducted to examine the effect of parameter variations on

Q^{*}

. The originality of this research lies in the application of the ES (μ + λ) algorithm to efficiently optimize order quantities of perishable products under a continuous review (Q, r) inventory policy.

过期易腐产品给企业带来了成本，有效的库存控制对于减少浪费和提高盈利能力至关重要。本文提出了一种持续评审（Q,r）库存策略下，具有固定寿命、随机需求和正交货期的易腐产品最优订货数量的数学模型。与传统模型不同，该方法将过时成本纳入总预期成本计算中。考虑到模型的计算复杂度，采用演化策略（μ + λ）优化算法，以最小的总期望成本对订货数量（Q*）进行优化。以泰国一家医院血库为例，进行了数值实验。通过灵敏度分析考察参数变化对Q*的影响。本研究的独创性在于应用ES （μ + λ）算法，在连续评审（Q, r）库存策略下有效优化易腐产品的订单数量。

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引用次数: 0

A predict-and-prescribe framework for dynamic course scheduling toward strategic university scaling 面向高校战略规模化的动态课程排课预测与规范框架

IF 7.2 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-01-01 Epub Date: 2025-08-06 DOI: 10.1016/j.omega.2025.103406

Özge Aygül , Teodor Hellgren , Shima Azizi , Andrew C. Trapp

Universities play vital roles in educating current and future generations. Universities that intend to survive in competitive academic markets where there are evolving enrollment trends must responsibly manage resources. Planning processes for instructional spaces can benefit from optimization and lead to more effective resource utilization, yet the use of trends in major and course demands to inform long-term planning remains largely unexplored. We propose a novel mathematical optimization framework that appears to be the first to use trend predictions to guide long-term dynamic course scheduling decisions and effective resource allocation. We begin with a baseline formulation that assigns course sections to time patterns and classroom spaces while considering instructor preferences, as well as constraints related to conflicts and capacity. We then extend this to a dynamic formulation that addresses bottleneck courses while prioritizing classroom utilization and honoring instructor preferences. Our dynamic formulation optimizes instructional space allocation for an academic period over the entire university, and solving for sequential independent academic periods reveals valuable insights into the efficiency of physical resource utilization on the horizon. Our framework is flexible, accommodating the objectives of faculty, schedulers, and administrators through a hierarchical multi-objective approach that integrates these diverse priorities. Our formulation addresses 76% and 81% of bottleneck sections for back-to-back semesters, with a substantial number of unutilized locations that could potentially be repurposed to accommodate the remaining bottleneck sections or other purposes. Through extensive experiments with varying university enrollment scenarios, we examine the resulting tradeoffs among objectives and highlight a variety of implications.

大学在教育当代人和后代方面发挥着至关重要的作用。大学要想在竞争激烈的学术市场中生存下来，就必须负责任地管理资源。教学空间的规划过程可以从优化中受益，并导致更有效的资源利用，然而，利用专业和课程需求的趋势来为长期规划提供信息，在很大程度上仍未得到探索。我们提出了一个新的数学优化框架，似乎是第一个使用趋势预测来指导长期动态课程调度决策和有效的资源分配。我们从一个基线公式开始，在考虑教师偏好以及与冲突和能力相关的约束的同时，将课程部分分配给时间模式和教室空间。然后，我们将其扩展为一个动态公式，在优先考虑课堂利用率和尊重教师偏好的同时，解决瓶颈课程。我们的动态公式优化了整个大学一个学术时期的教学空间分配，并解决了连续的独立学术时期，揭示了对未来物理资源利用效率的宝贵见解。我们的框架是灵活的，通过整合这些不同优先级的分层多目标方法来适应教师，调度人员和管理员的目标。我们的配方可以解决连续两个学期76%和81%的瓶颈段，大量未利用的位置可以重新利用，以容纳剩余的瓶颈段或其他目的。通过对不同大学招生情况的广泛实验，我们检查了目标之间的权衡，并强调了各种含义。

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引用次数: 0

Optimal self-scheduling and market involvement with electricity price uncertainty 电价不确定性下的最优自调度与市场参与

IF 6.7 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-01-01 Epub Date: 2025-07-21 DOI: 10.1016/j.omega.2025.103372

Mengling Zhang , Lun Ran , Jianzhi Leng

With increasing electricity market complexity and electricity price volatility, self-scheduling and market involvement problem has become a significant challenge for power producers. Instead of previous studies focusing solely on single-market optimization problem, we propose a self-scheduling and market involvement problem that integrates both the forward market and the spot market under price uncertainty. In our approach, the forward market determines unit commitment and electricity transaction decisions for future periods, while the spot market dictates generation scheduling and real-time electricity transaction. The objective is to maximize profit from both markets, while managing the risks associated with price uncertainty using the mean conditional value-at-risk (mean-CVaR). This risk measure captures the potential losses in profit over all spot price distributions, enabling a balance between profit maximization and risk aversion. To address electricity price uncertainty, we introduce two distributionally robust optimization (DRO) models. The first, M-DRO, utilizes the mean, support, and mean absolute deviation to define the ambiguity set, ensuring tractable and efficient optimization. The second, W-DRO, employs the 1-Wasserstein distance to capture more complex and data-driven uncertainties. A decomposition-based algorithm is proposed to solve the reformulated max–min problems. Extensive numerical experiments compare the performance of the proposed DRO models against traditional stochastic programming methods, providing key managerial insights for power producers in multi-market involvement.

随着电力市场复杂性和电价波动性的增加，自调度和市场参与问题已成为电力企业面临的重大挑战。与以往研究单一市场优化问题不同，本文提出了价格不确定条件下远期市场与现货市场相结合的自调度和市场参与问题。在我们的方法中，远期市场决定了未来一段时间的单位承诺和电力交易决策，而现货市场决定了发电计划和实时电力交易。目标是从两个市场中获得最大利润，同时使用平均条件风险价值（mean- cvar）管理与价格不确定性相关的风险。这种风险度量方法捕捉了所有现货价格分布中潜在的利润损失，在利润最大化和风险规避之间实现了平衡。为了解决电价的不确定性，我们引入了两个分布式鲁棒优化（DRO）模型。第一种是M-DRO，它利用均值、支持度和均值绝对偏差来定义歧义集，确保了易于处理和高效的优化。第二个是W-DRO，它利用1-Wasserstein距离来捕捉更复杂和数据驱动的不确定性。提出了一种基于分解的算法来求解重新表述的极大极小问题。大量的数值实验比较了所提出的DRO模型与传统随机规划方法的性能，为参与多市场的电力生产商提供了关键的管理见解。

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引用次数: 0

Opaque pricing strategy with social network effects 具有社会网络效应的不透明定价策略

IF 6.7 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-01-01 Epub Date: 2025-06-09 DOI: 10.1016/j.omega.2025.103362

Tengfei Nie , Hengjia Bao , Rongji Huang , Shaofu Du

Several payment platforms have recently implemented new forms of opaque discount policies, however, merchants do not have a clear dominant strategy. This paper first studies the impact of a social network on the opaque pricing strategies of a monopolistic merchant in an e-commerce market. We present a two-stage pricing-consumption game in which the merchant and consumers interact on a social network. In this setting, the monopolistic merchant chooses an optimal opaque discount strategy with full knowledge of consumer characteristics and the social network structure. The consumers, facing this opaque pricing policy, purchase optimal amounts of goods based on maximizing utility. Additionally, this paper introduces a series of bounded opaque discount disclosure strategies and determines the optimal strategy for merchants when consumers have different beliefs. Specifically, when consumers have strong beliefs about bounded opaque discounts, merchants should disclose the upper bound of the discount, and when consumer beliefs are weaker, the lower bound should be disclosed. Furthermore, we also explore individual consumer behavioral biases, such as overconfidence and fairness concerns, and their interactions with social networks on merchants’ opaque discount strategies. The findings indicate that merchants can leverage an understanding of consumer social network structures to implement strategic price discrimination targeting consumers with bounded rationality. However, the presence of these behavioral biases does not necessarily lead to an increase in profits gained by merchants through social networks.

一些支付平台最近实施了新形式的不透明折扣政策，然而，商家并没有一个明确的主导战略。本文首先研究了社会网络对电子商务市场中垄断商家不透明定价策略的影响。我们提出了一个两阶段的定价-消费博弈，其中商家和消费者在社交网络上进行互动。在这种情况下，垄断商家在充分了解消费者特征和社会网络结构的情况下，选择了最优的不透明折扣策略。面对这种不透明的定价政策，消费者在效用最大化的基础上购买最优数量的商品。此外，本文还引入了一系列有界不透明折扣披露策略，确定了在消费者信念不同时商家的最优策略。具体而言，当消费者对有界不透明折扣的信念较强时，商家应披露折扣的上界，当消费者信念较弱时，应披露折扣的下界。此外，我们还探讨了个人消费者的行为偏见，如过度自信和公平问题，以及它们与社交网络对商家不透明折扣策略的相互作用。研究结果表明，商家可以利用对消费者社会网络结构的理解，针对有限理性消费者实施战略性价格歧视。然而，这些行为偏差的存在并不一定会导致商家通过社交网络获得的利润增加。

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引用次数: 0

A bilevel approach to integrated surgeon scheduling and surgery planning solved via branch-and-price 一种基于分支和价格的双层外科医生调度和手术计划集成方法

IF 7.2 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-01-01 Epub Date: 2025-09-12 DOI: 10.1016/j.omega.2025.103424

Broos Maenhout , Přemysl Šůcha , Viktorie Valdmanova , Ondřej Tkadlec , Jana Thao Rozlivkova

In this paper, we study a multi-agent scheduling problem for organising the operations within the operating room department. The head of the surgeon group and individual surgeons are together responsible for the surgeon schedule and surgical case planning. The surgeon head allocates time blocks to individual surgeons, whereas individual surgeons determine the planning of surgical cases independently, which might degrade the schedule quality envisaged by the surgeon head. The bilevel optimisation under study seeks an optimal Nash equilibrium solution – a surgeon schedule and surgical case plan that optimise the objectives of the surgeon head, while ensuring that no individual surgeon can improve their own objective within the allocated time blocks. We propose a dedicated branch-and-price that adds lazy constraints to the formulation of surgeon-specific pricing problems to ensure an optimal bilevel feasible solution is retrieved. In this way, the surgeon head respects the objective requirements of the individual surgeons and the solution space can be searched efficiently. In the computational experiments, we validate the performance of the proposed algorithm and its dedicated components and provide insights into the benefits of attaining an equilibrium solution under different scenarios by calculating the price of stability and the price of decentralisation.

本文研究了一个多智能体组织手术室手术室作业的调度问题。手术组组长和个体外科医生共同负责手术时间表和手术病例计划。外科主任将时间块分配给单个外科医生，而单个外科医生独立决定手术病例的计划，这可能会降低外科主任设想的时间表质量。研究中的双层优化寻求最优纳什均衡解决方案-外科医生时间表和手术病例计划，以优化外科医生负责人的目标，同时确保每个外科医生都不能在分配的时间块内提高自己的目标。我们提出了一个专门的分支和价格，在特定外科医生定价问题的公式中添加惰性约束，以确保检索到最优的双层可行解决方案。这样，术者头部就尊重了术者个体的客观要求，并能有效地搜索到解空间。在计算实验中，我们验证了所提出的算法及其专用组件的性能，并通过计算稳定的价格和去中心化的价格，提供了在不同情况下获得均衡解决方案的好处。

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引用次数: 0

Optimal production, fuel economy investment and credit trading decisions under dual-credit policy 双信用政策下的最优生产、燃油经济性投资和信用交易决策

IF 6.7 2区管理学 Q1 MANAGEMENT

Omega-international Journal of Management Science

Pub Date : 2026-01-01 Epub Date: 2025-07-10 DOI: 10.1016/j.omega.2025.103375

Zhenxiao Wang , Fen Xu , Li Xiao , Peng Yang

We study a production system that produces FVs and NEVs during one selling season under the dual-credit policy (DCP), which is issued to reduce the greenhouse emissions generated from production. One specific feature of our model is that production generates two credits, either positive or negative, and DCP requires nonnegative credits at the end of the selling season and penalizes the negative credits. We show that the optimal production, fuel economy investment, and credit trading decisions depend on the initial capability of generating credits. Based on the optimal decisions, we find that DCP promotes the production of automakers who sell credits and reduces the production of automakers who purchase credits. We next discuss various factors affecting the optimal decisions and the effectiveness of DCP. In particular, a high initial capability to generate positive credits induces a high profit and large production quantity. A high credit purchasing price induces a low profit and a small credit trading volume. However, the optimal fuel economy decision and the credit trading decision are non-monotone in the initial capability to generate credits, and the production quantity and the fuel economy investment are non-monotone in the credit purchasing price.

我们研究了在双重信用政策（DCP）下，在一个销售季节生产fv和新能源汽车的生产系统，该政策旨在减少生产过程中产生的温室气体排放。我们模型的一个具体特征是，生产产生两种积分，要么是正积分，要么是负积分，DCP要求在销售季节结束时获得非负积分，并惩罚负积分。我们证明了最优的生产、燃油经济性投资和信用交易决策取决于产生信用的初始能力。基于最优决策，我们发现DCP促进了销售信用的汽车制造商的生产，减少了购买信用的汽车制造商的生产。接下来，我们将讨论影响DCP最优决策和有效性的各种因素。特别是，产生正信贷的高初始能力会导致高利润和大量生产。信用购买价格高，利润低，信用交易量小。而最优燃油经济性决策和信用交易决策在初始信用生成能力上是非单调的，生产数量和燃油经济性投资在信用购买价格上是非单调的。

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引用次数: 0