The curse of dimensionality has long been one of the biggest challenges in solving large-scale simulation ranking and selection (R&S) problems. As the number of systems grows, existing approaches to R&S relying on the Bonferroni correction become increasingly conservative, rendering them overachieving in error control and consuming more computational resources than necessary. In “Bonferroni-Free and Indifference-Zone-Flexible Sequential Elimination Procedures for Ranking and Selection,” Wang, Wan, and Chen develop Bonferroni-free and indifference-zone-optional ranking and selection procedures to deliver the prescribed probabilistic guarantee without overshooting. Their approach is to conduct always valid and fully sequential hypothesis tests that enable continuous monitoring of each candidate system and control the probability of correct selection. In addition, the indifference-zone parameter becomes dispensable in their procedures; however, when provided appropriately, it could improve the procedures’ computational and statistical efficiency.
长期以来，维数诅咒一直是解决大规模仿真排序和选择问题的最大挑战之一。随着系统数量的增长，依赖Bonferroni校正的现有R&S方法变得越来越保守，使得它们在错误控制方面取得了过高的成绩，并且消耗了不必要的计算资源。在“Bonferroni-Free and indifferential -zone- flexible Sequential Elimination Procedures for Ranking and Selection”中，Wang、Wan和Chen开发了Bonferroni-Free and indifferential -zone-optional Ranking and Selection程序，以提供规定的概率保证而不超调。他们的方法是进行始终有效且完全顺序的假设检验，从而能够持续监测每个候选系统并控制正确选择的概率。此外，在它们的过程中，无差异区参数变得可有可无;但是，如果提供适当，它可以提高程序的计算和统计效率。
{"title":"Bonferroni-Free and Indifference-Zone-Flexible Sequential Elimination Procedures for Ranking and Selection","authors":"Wenyu Wang, Hong Wan, Xi Chen","doi":"10.1287/opre.2023.2447","DOIUrl":"https://doi.org/10.1287/opre.2023.2447","url":null,"abstract":"The curse of dimensionality has long been one of the biggest challenges in solving large-scale simulation ranking and selection (R&S) problems. As the number of systems grows, existing approaches to R&S relying on the Bonferroni correction become increasingly conservative, rendering them overachieving in error control and consuming more computational resources than necessary. In “Bonferroni-Free and Indifference-Zone-Flexible Sequential Elimination Procedures for Ranking and Selection,” Wang, Wan, and Chen develop Bonferroni-free and indifference-zone-optional ranking and selection procedures to deliver the prescribed probabilistic guarantee without overshooting. Their approach is to conduct always valid and fully sequential hypothesis tests that enable continuous monitoring of each candidate system and control the probability of correct selection. In addition, the indifference-zone parameter becomes dispensable in their procedures; however, when provided appropriately, it could improve the procedures’ computational and statistical efficiency.","PeriodicalId":49809,"journal":{"name":"Military Operations Research","volume":"273 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83035116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Regret minimization has gained popularity in a wide range of decision-making problems under uncertainty because of its capacity to identify more opportunistic solutions than worst-case value optimization. Unfortunately, the rigidity of current worst-case regret models and scarcity of tractable solution methods have been serious obstacles in multistage applications. In “Risk-Averse Regret Minimization in Multistage Stochastic Programs,” M. Poursoltani, E. Delage, and A. Georghiou consider a multistage stochastic programming setting with a discrete scenario tree. They introduce the notion of the Δ-regret model, which bridges between the ex ante and ex post regret minimization paradigms that are currently used in the regret minimization literature for single-stage problems. The notion of Δ-regret minimization is investigated for the first time both theoretically and numerically in order to better understand its behavior under a set of popular risk measures.
由于后悔最小化算法比最坏情况值优化算法更能识别机会主义的解决方案，因此在不确定条件下的决策问题中得到了广泛的应用。然而，目前最坏情况后悔模型的刚性和可处理的求解方法的缺乏已经成为多阶段应用的严重障碍。M. Poursoltani, E. Delage和a . Georghiou在“多阶段随机规划中的风险规避遗憾最小化”一文中考虑了具有离散情景树的多阶段随机规划设置。他们引入了Δ-regret模型的概念，该模型连接了目前在单阶段问题的后悔最小化文献中使用的事前和事后后悔最小化范式。本文首次从理论上和数值上研究了Δ-regret最小化的概念，以便更好地理解它在一组流行的风险度量下的行为。
{"title":"Risk-Averse Regret Minimization in Multistage Stochastic Programs","authors":"Mehran Poursoltani, E. Delage, A. Georghiou","doi":"10.1287/opre.2022.2429","DOIUrl":"https://doi.org/10.1287/opre.2022.2429","url":null,"abstract":"Regret minimization has gained popularity in a wide range of decision-making problems under uncertainty because of its capacity to identify more opportunistic solutions than worst-case value optimization. Unfortunately, the rigidity of current worst-case regret models and scarcity of tractable solution methods have been serious obstacles in multistage applications. In “Risk-Averse Regret Minimization in Multistage Stochastic Programs,” M. Poursoltani, E. Delage, and A. Georghiou consider a multistage stochastic programming setting with a discrete scenario tree. They introduce the notion of the Δ-regret model, which bridges between the ex ante and ex post regret minimization paradigms that are currently used in the regret minimization literature for single-stage problems. The notion of Δ-regret minimization is investigated for the first time both theoretically and numerically in order to better understand its behavior under a set of popular risk measures.","PeriodicalId":49809,"journal":{"name":"Military Operations Research","volume":"76 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76708890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maxence Delorme, Sergio García, J. Gondzio, J. Kalcsics, D. Manlove, William Pettersson
New Exact Approaches Tailored for Kidney Exchange Programs with Hierarchical Objectives Kidney exchange programs increase the rate of living donor kidney transplantation. Whereas effective integer programming models aimed at maximizing the total number of transplants have been proposed in the literature, these cannot always be extended to handle a hierarchy of objectives, which is often a requirement in practice. In “New Algorithms for Hierarchical Optimization in Kidney Exchange Programs,” Delorme, García, Gondzio, Kalcsics, Manlove, and Pettersson introduce a new integer programming framework to solve large-size instances of kidney exchange programs. The authors use an ad hoc preprocessing and a reduced-cost variable fixing algorithm to dramatically decrease the size of the models, and they devise a diving algorithm that exploits the hierarchical structure of the problem to significantly reduce the number of integer programs that need to be solved. They also show that it is possible to transition between models as different layers are traversed in the hierarchy, allowing each layer to be solved with the most effective model. Experiments on three different European kidney exchange programs show that running times can be reduced by up to three orders of magnitude.
{"title":"New Algorithms for Hierarchical Optimization in Kidney Exchange Programs","authors":"Maxence Delorme, Sergio García, J. Gondzio, J. Kalcsics, D. Manlove, William Pettersson","doi":"10.1287/opre.2022.2374","DOIUrl":"https://doi.org/10.1287/opre.2022.2374","url":null,"abstract":"New Exact Approaches Tailored for Kidney Exchange Programs with Hierarchical Objectives Kidney exchange programs increase the rate of living donor kidney transplantation. Whereas effective integer programming models aimed at maximizing the total number of transplants have been proposed in the literature, these cannot always be extended to handle a hierarchy of objectives, which is often a requirement in practice. In “New Algorithms for Hierarchical Optimization in Kidney Exchange Programs,” Delorme, García, Gondzio, Kalcsics, Manlove, and Pettersson introduce a new integer programming framework to solve large-size instances of kidney exchange programs. The authors use an ad hoc preprocessing and a reduced-cost variable fixing algorithm to dramatically decrease the size of the models, and they devise a diving algorithm that exploits the hierarchical structure of the problem to significantly reduce the number of integer programs that need to be solved. They also show that it is possible to transition between models as different layers are traversed in the hierarchy, allowing each layer to be solved with the most effective model. Experiments on three different European kidney exchange programs show that running times can be reduced by up to three orders of magnitude.","PeriodicalId":49809,"journal":{"name":"Military Operations Research","volume":"70 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82039481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In Dynamic Pricing with Customer State Dependence, Wen Chen, Ying He, and Saurabh Bansal discuss optimal prices that a firm should offer to customers who develop a habit or satiation from consumption. At a high discount (or equivalently a lower price), a habit-prone customer will purchase a large amount in a current period. The firm will earn a low revenue per unit on the amount bought by the customer in this period. However, this large purchase will also create a stronger habit in the customer that the firm can exploit in the future periods. At a low discount, the firm will earn a higher per unit revenue in this period. However, the lower purchase quantity will also result in a weaker habit in the customer for the future periods. This tradeoff exists in every period. These effects are reversed for a satiation-prone customer. Using an analytical model, the authors determine the optimal profit-maximizing dynamic prices that a firm should offer to such habit- or satiation-prone customers. The results are robust for various specifications for habit formation, and yet in each specification they are obtainable tractably.
{"title":"Customized Dynamic Pricing When Customers Develop a Habit or Satiation","authors":"Wen Chen, Ying He, S. Bansal","doi":"10.1287/opre.2022.2412","DOIUrl":"https://doi.org/10.1287/opre.2022.2412","url":null,"abstract":"In Dynamic Pricing with Customer State Dependence, Wen Chen, Ying He, and Saurabh Bansal discuss optimal prices that a firm should offer to customers who develop a habit or satiation from consumption. At a high discount (or equivalently a lower price), a habit-prone customer will purchase a large amount in a current period. The firm will earn a low revenue per unit on the amount bought by the customer in this period. However, this large purchase will also create a stronger habit in the customer that the firm can exploit in the future periods. At a low discount, the firm will earn a higher per unit revenue in this period. However, the lower purchase quantity will also result in a weaker habit in the customer for the future periods. This tradeoff exists in every period. These effects are reversed for a satiation-prone customer. Using an analytical model, the authors determine the optimal profit-maximizing dynamic prices that a firm should offer to such habit- or satiation-prone customers. The results are robust for various specifications for habit formation, and yet in each specification they are obtainable tractably.","PeriodicalId":49809,"journal":{"name":"Military Operations Research","volume":"14 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80591065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scheduling Advertising on Cable Television Advertisement scheduling is a daily essential operational process in the television business. Efficient distribution of viewers among advertisers allows the television network to satisfy contracts and increase ad sale revenues. Ad scheduling is a challenging multiperiod, mixed-integer programming problem in which the network must create schedules to meet advertisers’ campaign goals and maximize ad revenues. Each campaign must meet a specific target group of viewers and a unique set of constraints. Moreover, the number of viewers is uncertain. To solve this problem, S. Souyris, S. Seshadri, and S. Subramanian develop and implement a practical approach that combines mathematical programming and machine learning to create daily schedules. According to standard business metrics and the small integer programming gap, these schedules are of high quality. Using their methods, leading networks in the United States and India experience a 3% to 5% revenue increase, which translates to about $60 million annually for one prominent user.
有线电视广告调度广告调度是电视业务中必不可少的日常操作过程。观众在广告商之间的有效分配使电视网络能够满足合同并增加广告销售收入。广告调度是一个具有挑战性的多周期，混合整数规划问题，其中网络必须创建时间表，以满足广告商的活动目标和最大化广告收入。每个活动都必须满足特定的目标受众群体和一组独特的约束条件。此外，观众的数量是不确定的。为了解决这个问题，S. Souyris, S. Seshadri和S. Subramanian开发并实施了一种实用的方法，将数学编程和机器学习相结合，以创建日常时间表。根据标准的业务指标和较小的整数规划差距，这些计划是高质量的。使用他们的方法，美国和印度的主要网络的收入增加了3%至5%，这意味着一个知名用户每年可以获得约6,000万美元的收入。
{"title":"Scheduling Advertising on Cable Television","authors":"S. Souyris, Sridhar Seshadri, Sriram Subramanian","doi":"10.1287/opre.2022.2430","DOIUrl":"https://doi.org/10.1287/opre.2022.2430","url":null,"abstract":"Scheduling Advertising on Cable Television Advertisement scheduling is a daily essential operational process in the television business. Efficient distribution of viewers among advertisers allows the television network to satisfy contracts and increase ad sale revenues. Ad scheduling is a challenging multiperiod, mixed-integer programming problem in which the network must create schedules to meet advertisers’ campaign goals and maximize ad revenues. Each campaign must meet a specific target group of viewers and a unique set of constraints. Moreover, the number of viewers is uncertain. To solve this problem, S. Souyris, S. Seshadri, and S. Subramanian develop and implement a practical approach that combines mathematical programming and machine learning to create daily schedules. According to standard business metrics and the small integer programming gap, these schedules are of high quality. Using their methods, leading networks in the United States and India experience a 3% to 5% revenue increase, which translates to about $60 million annually for one prominent user.","PeriodicalId":49809,"journal":{"name":"Military Operations Research","volume":"106 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88090746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Antoine Désir, Vineet Goyal, Bo Jiang, Tian Xie, Jiawei Zhang
Robust Assortment Optimization Under the Markov Chain Choice Model Assortment optimization arises widely in many practical applications. In this problem, the goal is to select products to offer customers in order to maximize the expected revenue. We study a robust assortment-optimization problem under the Markov chain choice model, in which the parameters of the choice model are assumed to be uncertain, and the goal is to maximize the worst case expected revenue over all parameter values in an uncertainty set. Our main contribution is to prove a min-max duality result when the uncertainty set is row-wise. The result is surprising as the objective function does not satisfy the properties usually needed for known min-max results. Inspired by the duality result, we develop an efficient iterative algorithm for computing the optimal robust assortment under the Markov chain choice model. Moreover, our results yield operational insights into the effect of changing the uncertainty set on the optimal robust assortment.
{"title":"Robust Assortment Optimization Under the Markov Chain Choice Model","authors":"Antoine Désir, Vineet Goyal, Bo Jiang, Tian Xie, Jiawei Zhang","doi":"10.1287/opre.2022.2420","DOIUrl":"https://doi.org/10.1287/opre.2022.2420","url":null,"abstract":"Robust Assortment Optimization Under the Markov Chain Choice Model Assortment optimization arises widely in many practical applications. In this problem, the goal is to select products to offer customers in order to maximize the expected revenue. We study a robust assortment-optimization problem under the Markov chain choice model, in which the parameters of the choice model are assumed to be uncertain, and the goal is to maximize the worst case expected revenue over all parameter values in an uncertainty set. Our main contribution is to prove a min-max duality result when the uncertainty set is row-wise. The result is surprising as the objective function does not satisfy the properties usually needed for known min-max results. Inspired by the duality result, we develop an efficient iterative algorithm for computing the optimal robust assortment under the Markov chain choice model. Moreover, our results yield operational insights into the effect of changing the uncertainty set on the optimal robust assortment.","PeriodicalId":49809,"journal":{"name":"Military Operations Research","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91153826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Paat Rusmevichientong, Mika Sumida, Huseyin Topaloglu, Yicheng Bai
There are a variety of revenue management systems that require making pricing or availability decisions for unique resources. For example, lodging marketplaces, boutique hotels, and bed-and-breakfasts offer unique rooms, apartments, or houses. Matching platforms for freelancers recommend differentiated workers with unique characteristics. When managing unique resources, one has to keep track of the availability of each resource at each time point in the future. Moreover, if the customers substitute between different resources, then the pricing and availability decisions for all resources become interdependent. Thus, it can be challenging to find good policies to make pricing or availability decisions. In “Revenue Management with Heterogeneous Resources: Unit Resource Capacities, Advance Bookings, and Itineraries over Time Intervals,” Rusmevichientong, Sumida, Topaloglu, and Bai consider revenue management problems when unique resources are requested for use over intervals of time under advance reservations. Using the interval structure of resource requests, they give policies with performance guarantees.
{"title":"Revenue Management with Heterogeneous Resources: Unit Resource Capacities, Advance Bookings, and Itineraries over Time Intervals","authors":"Paat Rusmevichientong, Mika Sumida, Huseyin Topaloglu, Yicheng Bai","doi":"10.1287/opre.2022.2427","DOIUrl":"https://doi.org/10.1287/opre.2022.2427","url":null,"abstract":"There are a variety of revenue management systems that require making pricing or availability decisions for unique resources. For example, lodging marketplaces, boutique hotels, and bed-and-breakfasts offer unique rooms, apartments, or houses. Matching platforms for freelancers recommend differentiated workers with unique characteristics. When managing unique resources, one has to keep track of the availability of each resource at each time point in the future. Moreover, if the customers substitute between different resources, then the pricing and availability decisions for all resources become interdependent. Thus, it can be challenging to find good policies to make pricing or availability decisions. In “Revenue Management with Heterogeneous Resources: Unit Resource Capacities, Advance Bookings, and Itineraries over Time Intervals,” Rusmevichientong, Sumida, Topaloglu, and Bai consider revenue management problems when unique resources are requested for use over intervals of time under advance reservations. Using the interval structure of resource requests, they give policies with performance guarantees.","PeriodicalId":49809,"journal":{"name":"Military Operations Research","volume":"28 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76417600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Can inefficiency be rational? Excess resources or slack may serve as a buffer against environmental shocks, help decouple organizations, ease planning and implementation, support innovation, and enable effective responses to competitors. Slack may however also be the result of inefficiency. In Bogetoft and Kerstens, Distinguishing useful and wasteful slack, we propose an approach to separate useful and wasteful slack. If an organization can maintain the same levels of output and slack at lower cost, there is wasteful or nonrationalizable spending. We develop ways to measure the extent to which total spending can be rationalized and show how to statistically estimate and test the usefulness of the available slack using bootstrapping.
{"title":"Distinguishing Useful and Wasteful Slack","authors":"P. Bogetoft, P. Kerstens","doi":"10.1287/opre.2022.2415","DOIUrl":"https://doi.org/10.1287/opre.2022.2415","url":null,"abstract":"Can inefficiency be rational? Excess resources or slack may serve as a buffer against environmental shocks, help decouple organizations, ease planning and implementation, support innovation, and enable effective responses to competitors. Slack may however also be the result of inefficiency. In Bogetoft and Kerstens, Distinguishing useful and wasteful slack, we propose an approach to separate useful and wasteful slack. If an organization can maintain the same levels of output and slack at lower cost, there is wasteful or nonrationalizable spending. We develop ways to measure the extent to which total spending can be rationalized and show how to statistically estimate and test the usefulness of the available slack using bootstrapping.","PeriodicalId":49809,"journal":{"name":"Military Operations Research","volume":"29 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86953563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Can Zhang, T. Ayer, Chelsea C. White, Joy N. Bodeker, J. Roback
A Simple and Provably Good Inventory Policy Led to a Significant Reduction in Platelet Outdates Platelets are critical blood products. The management of platelet inventory is particularly challenging because of its perishable nature with a short shelf life. This paper studies how the wastage of platelets and, more broadly, perishable products can be reduced through inventory sharing. The authors derive structural results on the optimal ordering and transshipment policies for a two-location perishable inventory system and prove that an easy-to-implement myopic transshipment policy is optimal for a few special cases relevant to practice and serves as a lower bound on the optimal transshipment policy for more general settings. This policy has been successfully implemented by the Emory University Hospital System, which led to a reduction of approximately 20% in platelet outdates. Moreover, this paper also sheds light on how the presence of inventory sharing affects the optimal ordering quantities and provides insights that significant depart from existing findings for nonperishable inventory systems.
{"title":"Inventory Sharing for Perishable Products: Application to Platelet Inventory Management in Hospital Blood Banks","authors":"Can Zhang, T. Ayer, Chelsea C. White, Joy N. Bodeker, J. Roback","doi":"10.1287/opre.2022.2410","DOIUrl":"https://doi.org/10.1287/opre.2022.2410","url":null,"abstract":"A Simple and Provably Good Inventory Policy Led to a Significant Reduction in Platelet Outdates Platelets are critical blood products. The management of platelet inventory is particularly challenging because of its perishable nature with a short shelf life. This paper studies how the wastage of platelets and, more broadly, perishable products can be reduced through inventory sharing. The authors derive structural results on the optimal ordering and transshipment policies for a two-location perishable inventory system and prove that an easy-to-implement myopic transshipment policy is optimal for a few special cases relevant to practice and serves as a lower bound on the optimal transshipment policy for more general settings. This policy has been successfully implemented by the Emory University Hospital System, which led to a reduction of approximately 20% in platelet outdates. Moreover, this paper also sheds light on how the presence of inventory sharing affects the optimal ordering quantities and provides insights that significant depart from existing findings for nonperishable inventory systems.","PeriodicalId":49809,"journal":{"name":"Military Operations Research","volume":"29 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74016101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Decision-making under simultaneous competition Hardly any decision is made in isolation and most decision makers are dealing with fierce competition when trying to find the optimal decision for their problem. The expected outcome of such a competitive problem setting or the individually optimal course of action for each competitor is not evident. In a finite game, a finite set of decision makers simultaneously select their action from a finite set of strategies. In “Equilibrium identification and selection in finite games”, T. Crönert and S. Minner propose a solution approach enumerating all equilibria and selecting the most likely equilibrium in finite games. The approach is targeted toward large finite games that cannot be efficiently represented in normal form. They apply their algorithm to two- and three-player knapsack and facility location and design games. Their numerical experiments show that prior approaches identifying a single equilibrium can result in unlikely outcomes.
{"title":"Equilibrium Identification and Selection in Finite Games","authors":"Tobias Crönert, S. Minner","doi":"10.1287/opre.2022.2413","DOIUrl":"https://doi.org/10.1287/opre.2022.2413","url":null,"abstract":"Decision-making under simultaneous competition Hardly any decision is made in isolation and most decision makers are dealing with fierce competition when trying to find the optimal decision for their problem. The expected outcome of such a competitive problem setting or the individually optimal course of action for each competitor is not evident. In a finite game, a finite set of decision makers simultaneously select their action from a finite set of strategies. In “Equilibrium identification and selection in finite games”, T. Crönert and S. Minner propose a solution approach enumerating all equilibria and selecting the most likely equilibrium in finite games. The approach is targeted toward large finite games that cannot be efficiently represented in normal form. They apply their algorithm to two- and three-player knapsack and facility location and design games. Their numerical experiments show that prior approaches identifying a single equilibrium can result in unlikely outcomes.","PeriodicalId":49809,"journal":{"name":"Military Operations Research","volume":"94 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91306664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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