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Lot-sizing and pricing decisions under attraction demand models and multi-channel environment: New efficient formulations 吸引-需求模型和多渠道环境下的批量和定价决策:新的高效配方
IF 2.5 4区 管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-01-01 DOI: 10.1016/j.orp.2023.100269
Mourad Terzi , Yassine Ouazene , Alice Yalaoui , Farouk Yalaoui

The presented paper considers the pricing and lot-sizing decisions for a manufacturer who produces and sells a single product in different selling channels i.e physical stock, website, mobile, etc. The objective is to find the production plan and prices of each channel to maximize the total profit defined from difference between the revenues and the productions, holding and setups costs. The consumers’ demand in each channel is represented by attraction demand models which include the multinomial logit (MNL), multiplicative competitive interaction (MCI) and linear demand models. The addressed problem is formulated as a non-convex mixed-integer nonlinear program (MINLP). Based on properties of attraction functions, an efficient reformulation which transforms the initial non-convex problem into a convex one is presented. Therefore, an optimization approach based on the outer approximation algorithm is presented to solve the problem. Numerical tests based on large benchmark of real inspired instances show the efficiency of the proposed approach to solve the addressed problem compared to the initial non-convex model.

本文考虑了制造商在不同的销售渠道(即实体库存,网站,移动等)生产和销售单一产品的定价和批量决策。目标是找到每个渠道的生产计划和价格,以最大限度地利用收入与生产、持有和设置成本之间的差额来定义总利润。各渠道的消费者需求由吸引需求模型表示,吸引需求模型包括多项logit (MNL)、乘法竞争交互(MCI)和线性需求模型。该问题被表述为一个非凸混合整数非线性规划(MINLP)。根据吸引函数的性质,给出了一种将初始非凸问题转化为凸问题的有效的重新表述。因此,提出了一种基于外部逼近算法的优化方法来解决这一问题。基于实际启发实例的大型基准数值测试表明,与初始非凸模型相比,所提出的方法能够有效地解决所处理的问题。
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引用次数: 0
Analysing the impact of COVID-19 pandemic on the psychological health of people using fuzzy MCDM methods 应用模糊MCDM方法分析新冠肺炎大流行对人群心理健康的影响
IF 2.5 4区 管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-01-01 DOI: 10.1016/j.orp.2022.100263
Shafi Ahmad , Sarfaraz Masood , Noor Zaman Khan , Irfan Anjum Badruddin , Ompal , Ali Ahmadian , Zahid A. Khan , Amil Hayat Khan

Recently, a large portion of the world's population has experienced an unprecedented devastating effect of the COVID-19 pandemic. At the time of its outbreak, not much was known about this disease and therefore, quarantine and social distancing were the only ways suggested to prevent its spread among humans. Although the current situation is much better than before however, strict social distancing norms as well as frequent long-lasting lockdowns with stringent guidelines and actions to control the spread in the early days have affected the physical and psychological health of the people. Consequently, this study was carried out to attain the following major objectives: (i) to identify the potential psychological problems/factors that might have been caused due to COVID-19 led social distancing and lockdowns, and (ii) to determine the ranks of the identified psychological factors to reflect their degree of criticality. The first objective was achieved by gathering information about the potential psychological factors from the experts. Data, in terms of linguistic variables, was collected from the experts and analyzed using two fuzzy-based multi-criteria decision-making (MCDM) methods i.e. Fuzzy Best Worst Method (F-BWM) and Fuzzy TOPSIS (F-TOPSIS) which led to the accomplishment of the second objective. The results of this study revealed that anxiety, stress, panic attacks, frustration, and insomnia were the top five critical psychological factors that might have affected people due to this pandemic. Consistency of the results was ensured by comparing the obtained ranks with the ranks found using the Fuzzy WSM and Fuzzy MABAC methods. In addition, the robustness of the results was ascertained by conducting the sensitivity analysis. Based on the findings of the study, the identified factors were categorized into most, average, and least critical psychological factors. This research might help the relevant authorities to understand the extent of the seriousness of the various psychological factors caused by this pandemic, so that an effective strategy may be developed for better management, control, and safety.

最近,世界上很大一部分人口遭受了COVID-19大流行前所未有的破坏性影响。在疫情爆发时,人们对这种疾病知之甚少,因此,隔离和保持社交距离是防止其在人类中传播的唯一方法。虽然目前的情况比以前好得多,但严格的社会距离规范和频繁的长期封锁,以及早期严格的指导方针和控制传播的行动,影响了人们的身心健康。因此,本研究旨在实现以下主要目标:(i)确定可能因COVID-19导致的社会距离和封锁而导致的潜在心理问题/因素;(ii)确定确定的心理因素的等级,以反映其严重程度。第一个目标是通过从专家那里收集有关潜在心理因素的信息来实现的。在语言变量方面,从专家那里收集数据,并使用两种基于模糊的多准则决策(MCDM)方法,即模糊最佳最差方法(F-BWM)和模糊TOPSIS (F-TOPSIS)进行分析,从而实现第二个目标。这项研究的结果显示,焦虑、压力、惊恐发作、沮丧和失眠是可能因这次大流行而影响人们的五大关键心理因素。通过将得到的秩与使用模糊WSM和模糊MABAC方法得到的秩进行比较,确保了结果的一致性。此外,通过进行敏感性分析来确定结果的稳健性。根据研究结果,确定的因素被分为最重要、一般和最不重要的心理因素。这项研究可能有助于有关当局了解由这次大流行引起的各种心理因素的严重程度,从而制定有效的战略,以更好地管理、控制和安全。
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引用次数: 7
Prescribing net demand for two-stage electricity generation scheduling 确定两阶段发电计划的净需求
IF 2.5 4区 管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-01-01 DOI: 10.1016/j.orp.2023.100268
J.M. Morales, M.A. Muñoz, S. Pineda

We consider a two-stage generation scheduling problem comprising a forward dispatch and a real-time re-dispatch. The former must be conducted facing an uncertain net demand that includes non-dispatchable electricity consumption and renewable power generation. The latter copes with the plausible deviations with respect to the forward schedule by making use of balancing power during the actual operation of the system. Standard industry practice deals with the uncertain net demand in the forward stage by replacing it with a good estimate of its conditional expectation (usually referred to as a point forecast), so as to minimize the need for balancing power in real time. However, it is well known that the cost structure of a power system is highly asymmetric and dependent on its operating point, with the result that minimizing the amount of power imbalances is not necessarily aligned with minimizing operating costs. In this paper, we propose a bilevel program to construct, from the available historical data, a prescription of the net demand that does account for the power system’s cost asymmetry. Furthermore, to accommodate the strong dependence of this cost on the power system’s operating point, we use clustering to tailor the proposed prescription to the foreseen net-demand regime. By way of an illustrative example and a more realistic case study based on the European power system, we show that our approach leads to substantial cost savings compared to the customary way of doing.

我们考虑了一个包括前向调度和实时重新调度的两阶段发电调度问题。前者必须面对不确定的净需求,包括不可调度的电力消耗和可再生能源发电。后者通过在系统的实际操作期间利用平衡功率来处理相对于前向时间表的合理偏差。标准行业实践通过用对其条件预期的良好估计(通常称为点预测)来代替前一阶段的不确定净需求,以最大限度地减少实时平衡电力的需要。然而,众所周知,电力系统的成本结构是高度不对称的,并取决于其运行点,因此,最小化电力失衡量并不一定与最小化运行成本一致。在本文中,我们提出了一个双层程序,根据可用的历史数据,构建一个考虑电力系统成本不对称的净需求处方。此外,为了适应这种成本对电力系统运行点的强烈依赖性,我们使用聚类来根据预测的净需求制度调整所提出的处方。通过一个说明性的例子和一个基于欧洲电力系统的更现实的案例研究,我们表明,与传统的做法相比,我们的方法节省了大量的成本。
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引用次数: 4
A robust model for emergency supplies prepositioning and transportation considering road disruptions 考虑道路中断的应急物资预先定位和运输的稳健模型
IF 2.5 4区 管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-01-01 DOI: 10.1016/j.orp.2023.100266
Wuyang Yu

Proper prepositioning of emergency supplies can dramatically improve the efficiency of emergency response work. However, the uncertainties of emergency demands and road conditions bring difficulties to the prepositioning of emergency supplies. This paper proposes a two-stage robust model to locate emergency supply points and preposition the corresponding storage amount of emergency supplies, in which we presented two budget sets to describe the uncertainties of demands and road conditions, respectively. The innovative use of variables in the model to limit road capacities addresses the representation of different road interruption scenarios. We proposed an algorithm based on Benders decomposition by transforming the second-stage model into a binary linear programming model. Computational experiments based on the Sioux Falls network demonstrate the validity of the model and algorithm. We conducted sensitivity analyses for some important parameters in the model, such as two uncertainty control parameters, unit transportation cost, budget for the construction of emergency supply points, etc. We find that the uncertainty of road disruptions has a greater impact on the model than the uncertainty of demands. In addition, when the control parameter of the road disruptions exceeds a certain threshold, its influence on the model remains essentially constant.

适当地预先部署应急物资可以极大地提高应急工作的效率。然而,应急需求和道路状况的不确定性给应急物资的预先部署带来了困难。本文提出了一个两阶段鲁棒模型来定位应急供应点并预先确定相应的应急物资储存量,其中我们分别提出了两个预算集来描述需求和道路状况的不确定性。模型中创新性地使用变量来限制道路通行能力,解决了不同道路中断场景的表示问题。我们提出了一种基于Benders分解的算法,将第二阶段模型转换为二元线性规划模型。基于Sioux-Falls网络的计算实验验证了模型和算法的有效性。我们对模型中的一些重要参数进行了敏感性分析,如两个不确定性控制参数、单位运输成本、应急供应点建设预算等。我们发现,道路中断的不确定性比需求的不确定性对模型的影响更大。此外,当道路中断的控制参数超过一定阈值时,其对模型的影响基本保持不变。
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引用次数: 0
Dynamic portfolio selection with linear control policies for coherent risk minimization 基于线性控制策略的动态投资组合选择
IF 2.5 4区 管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-01-01 DOI: 10.1016/j.orp.2022.100262
Yuichi Takano , Jun-ya Gotoh

This paper is concerned with a linear control policy for dynamic portfolio selection. We develop this policy by incorporating time-series behaviors of asset returns on the basis of coherent risk minimization. Analyzing the dual form of our optimization model, we demonstrate that the investment performance of linear control policies is directly connected to the intertemporal covariance of asset returns. To mitigate overfitting to training data (i.e., historical asset returns), we apply robust optimization. For this optimization, we prove that the worst-case coherent risk measure can be decomposed into the empirical risk measure and the penalty terms. Numerical results demonstrate that when the number of assets is small, linear control policies deliver good out-of-sample investment performance. When the number of assets is large, the penalty terms improve the out-of-sample investment performance.

研究动态投资组合选择的线性控制策略。我们通过在一致风险最小化的基础上结合资产回报的时间序列行为来制定这一政策。通过分析优化模型的对偶形式,我们证明了线性控制策略的投资绩效与资产收益的跨期协方差直接相关。为了减轻对训练数据的过度拟合(即,历史资产回报),我们应用了鲁棒优化。对于这种优化,我们证明了最坏情况下的相干风险度量可以分解为经验风险度量和惩罚项。数值结果表明,当资产数量较少时,线性控制策略具有良好的样本外投资绩效。当资产数量较大时,惩罚项改善了样本外投资绩效。
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引用次数: 1
A stochastic card balance management problem with continuous and batch-type bilateral transactions 具有连续批量双边交易的随机卡余额管理问题
IF 2.5 4区 管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-01-01 DOI: 10.1016/j.orp.2023.100274
Yonit Barron

We study a stochastic continuous-review card balance management problem with two transaction patterns, namely, continuous and batch-type bilateral transactions, both in a Markovian environment. Motivated by the Autoload program used in public transit systems, the card is managed using a two-parameter band policy. Our cost structure includes activation and loading costs, and a fine for a negative balance. By applying hitting time theory and martingales, we derive the cost functionals and obtain, numerically, the optimal thresholds minimizing the expected discounted total cost. Surprisingly, a numerical study shows that the optimal policy is inherently linked with the outflow patterns, and is more sensitive to changes in withdrawal rates than to changes in batch sizes. We further show that timing is a significant factor in determining the policy: a high discount factor leads to frequent activations with smaller amounts.

研究了马尔可夫环境下具有连续和批处理两种交易模式的随机连续复查卡余额管理问题。受公共交通系统中使用的自动加载程序的启发,该卡使用双参数频带策略进行管理。我们的成本结构包括激活和装载成本,以及负余额的罚款。运用命中时间理论和鞅方法,导出了代价函数,并在数值上求出了使期望折现总代价最小的最优阈值。令人惊讶的是,一项数值研究表明,最优策略与流出模式存在内在联系,并且对提取率的变化比批量大小的变化更敏感。我们进一步表明,时机是决定策略的一个重要因素:高折扣因子导致频繁的小额激活。
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引用次数: 1
SIR model for the spread of COVID-19: A case study 新冠肺炎传播的SIR模型:一个案例研究
IF 2.5 4区 管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2022-12-01 DOI: 10.1016/j.orp.2022.100265
A. Salimipour, Toktam Mehraban, Hevi Ghafour, N. Arshad, M. J. Ebadi
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引用次数: 7
An integer programming model for obtaining cyclic quasi-difference matrices 求循环拟差分矩阵的整数规划模型
IF 2.5 4区 管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2022-12-01 DOI: 10.1016/j.orp.2022.100260
Luis Martínez, María Merino, Juan Manuel Montoya
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引用次数: 0
Fleet sizing of trucks for an inter-facility material handling system using closed queueing networks 使用封闭排队网络的设施间物料搬运系统的卡车车队规模
IF 2.5 4区 管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2022-01-01 DOI: 10.1016/j.orp.2022.100245
Mohamed Amjath , Laoucine Kerbache , James MacGregor Smith , Adel Elomri

Material handling systems (MHS) are integral to logistics functions by providing various supports such as handling, moving, and storing materials in manufacturing and service organisations. This study considers determining the optimal size of a homogeneous fleet of trucks to be outsourced (or subcontracted) from a third-party logistics provider to be used daily to cyclically transport different types of raw materials from designated storage yards to intermediate buffer locations to be fed as inputs to a production facility for processing. Within this context, the problem is modelled as a closed queueing network (CQN) combined with mixed-integer nonlinear programming (MINLP) to determine the optimal fleet size. This study proposes an analytical method based on sequential quadratic programming (SQP) methodology coupled with a mean value analysis (MVA) algorithm to solve this NP-Hard problem. Furthermore, a discrete event simulation (DES) model is developed to validate the optimisation of non-dominant solutions. The proposed analytical approach, along with the simulation, are implemented in a real case study of a steel manufacturing setup. Analytical model results are validated using the simulation results, which are proved to be very accurate, with deviations ranges within ±7%.

物料搬运系统(MHS)是物流功能的组成部分,它为制造和服务组织提供各种支持,如搬运、移动和储存物料。本研究考虑确定从第三方物流供应商外包(或分包)的同质卡车车队的最佳规模,每天用于循环运输不同类型的原材料,从指定的储存场地到中间缓冲地点,作为输入馈送到生产设施进行加工。在此背景下,将该问题建模为封闭排队网络(CQN)与混合整数非线性规划(MINLP)相结合,以确定最优车队规模。本文提出了一种基于序列二次规划(SQP)的分析方法,并结合均值分析(MVA)算法来解决这一NP-Hard问题。此外,建立了一个离散事件模拟(DES)模型来验证非优势解的优化。提出的分析方法,连同模拟,在一个真实的钢铁制造装置的案例研究中实施。利用仿真结果对分析模型结果进行了验证,结果表明分析模型非常准确,误差范围在±7%以内。
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引用次数: 5
Integrated procurement-production inventory model in supply chain: A systematic review 供应链中采购-生产一体化库存模型的系统回顾
IF 2.5 4区 管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2022-01-01 DOI: 10.1016/j.orp.2022.100221
Dana Marsetiya Utama , Imam Santoso , Yusuf Hendrawan , Wike Agustin Prima Dania

Inventory affects the production process and supply chain activities. Integrated decision inventory improves performance and optimizes supply chain activities. However, its disadvantage is the Integrated Procurement Production (IPP) inventory model, which manages the raw material inventory in procurement activities, works in process, and finished products. This study reviewed the IPP inventory model problem using a systematic review of 102 published papers from 1992 to 2021. The reviewed papers were based on complexity, type of model, data, time dynamics, optimization, solution, and paper. This study presented the IPP inventory model analysis, gap, and future study directions.

库存影响着生产过程和供应链活动。集成决策库存提高了绩效并优化了供应链活动。然而,它的缺点是集成采购生产(IPP)库存模型,该模型管理采购活动中的原材料库存、在制品库存和成品库存。本研究对1992年至2021年发表的102篇论文进行了系统回顾,回顾了IPP库存模型问题。论文的评审按复杂性、模型类型、数据、时间动态、优化、解决方案和论文进行。本研究提出了IPP库存模型的分析、差距和未来的研究方向。
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引用次数: 25
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Operations Research Perspectives
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