Healthcare providers have long grappled with patients not showing up for their scheduled medical appointments; such no-shows lead to wasted resources and longer wait times for other patients. However, new operations research offers a promising solution to this problem. The study finds that using text message reminders that include an additional line of text indicating a potentially long wait for the next available appointment can significantly reduce no-shows by a factor of 28.6%. The intervention, called waits framing, was found to be more effective among patients who were more sensitive to wait times and when the information in the message was novel and credible. The study also uncovered the mechanism underlying the intervention. Specifically, the waits framing messages increased the perceived cost of missing an appointment, leading to a reduction in queue abandonment. This study provides insights into how behavioral science can improve service operations and help tackle challenges in healthcare delivery.
{"title":"Nudging Patient Choice: Reducing No-Shows Using Waits Framing Messaging","authors":"Jiayi Liu, KC DiwasSingh","doi":"10.1287/opre.2023.2444","DOIUrl":"https://doi.org/10.1287/opre.2023.2444","url":null,"abstract":"Healthcare providers have long grappled with patients not showing up for their scheduled medical appointments; such no-shows lead to wasted resources and longer wait times for other patients. However, new operations research offers a promising solution to this problem. The study finds that using text message reminders that include an additional line of text indicating a potentially long wait for the next available appointment can significantly reduce no-shows by a factor of 28.6%. The intervention, called waits framing, was found to be more effective among patients who were more sensitive to wait times and when the information in the message was novel and credible. The study also uncovered the mechanism underlying the intervention. Specifically, the waits framing messages increased the perceived cost of missing an appointment, leading to a reduction in queue abandonment. This study provides insights into how behavioral science can improve service operations and help tackle challenges in healthcare delivery.","PeriodicalId":19546,"journal":{"name":"Oper. Res.","volume":"53 1","pages":"1004-1020"},"PeriodicalIF":0.0,"publicationDate":"2023-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91240020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
How Product Locations Drive Traffic Throughout a Retail Store In “Store-Wide Shelf-Space Allocation with Ripple Effects Driving Traffic,” Flamand, Ghoniem, and Maddah develop a framework for deciding where to place products in a store, in addition to apportioning the shelf space among products, in a way that maximizes impulse profit, a phenomenon that may account for 50% of transactions. By analyzing a large data set of customer receipts from a grocery store in Beirut, the authors develop a regression model that estimates traffic at a shelf based on its location and the “attraction” from products allocated nearby. The traffic model is embedded within a mixed-integer nonlinear program, which they solve via specialized linear approximations. For the store in Beirut, a 65% improvement in impulse profit is anticipated, and the location of products is found to be significantly more important in driving store-wide traffic than the relative shelf-space allocation.
{"title":"Store-Wide Shelf-Space Allocation with Ripple Effects Driving Traffic","authors":"Tulay Flamand, A. Ghoniem, B. Maddah","doi":"10.1287/opre.2023.2437","DOIUrl":"https://doi.org/10.1287/opre.2023.2437","url":null,"abstract":"How Product Locations Drive Traffic Throughout a Retail Store In “Store-Wide Shelf-Space Allocation with Ripple Effects Driving Traffic,” Flamand, Ghoniem, and Maddah develop a framework for deciding where to place products in a store, in addition to apportioning the shelf space among products, in a way that maximizes impulse profit, a phenomenon that may account for 50% of transactions. By analyzing a large data set of customer receipts from a grocery store in Beirut, the authors develop a regression model that estimates traffic at a shelf based on its location and the “attraction” from products allocated nearby. The traffic model is embedded within a mixed-integer nonlinear program, which they solve via specialized linear approximations. For the store in Beirut, a 65% improvement in impulse profit is anticipated, and the location of products is found to be significantly more important in driving store-wide traffic than the relative shelf-space allocation.","PeriodicalId":19546,"journal":{"name":"Oper. Res.","volume":"28 1","pages":"1073-1092"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74768299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Effective management of demand risk is a central problem of production planning. In many applications, it is observed that demand often depends on certain asset prices in the financial market. This calls for a model that jointly optimizes the production decision along with a risk hedging policy, using the latter to compensate for loss of profit in scenarios of weak demand. In “Production Planning with Risk Hedging under a Conditional Value at Risk Objective,” Wang and Yao develop an integrated production and risk hedging model, where the risk hedging strategy is derived in explicit form and the production quantity is solved as a concave maximization problem. Furthermore, a complete characterization of the efficient frontier is provided, and the improvement over the production-only decision is quantified.
{"title":"Production Planning with Risk Hedging Under a Conditional Value at Risk Objective","authors":"Liao Wang, D. Yao","doi":"10.1287/opre.2022.2423","DOIUrl":"https://doi.org/10.1287/opre.2022.2423","url":null,"abstract":"Effective management of demand risk is a central problem of production planning. In many applications, it is observed that demand often depends on certain asset prices in the financial market. This calls for a model that jointly optimizes the production decision along with a risk hedging policy, using the latter to compensate for loss of profit in scenarios of weak demand. In “Production Planning with Risk Hedging under a Conditional Value at Risk Objective,” Wang and Yao develop an integrated production and risk hedging model, where the risk hedging strategy is derived in explicit form and the production quantity is solved as a concave maximization problem. Furthermore, a complete characterization of the efficient frontier is provided, and the improvement over the production-only decision is quantified.","PeriodicalId":19546,"journal":{"name":"Oper. Res.","volume":"111 1","pages":"1055-1072"},"PeriodicalIF":0.0,"publicationDate":"2023-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73412565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Crowds management during peak commuting hours is a key challenge facing metro systems worldwide, which results in serious safety concerns and unfair public transit service for commuters on different origin-destination (o-d) pairs. In “Online Passenger Flow Control in Metro Lines,” the authors investigate the impact of online decision making on the value of passenger flow control solution methodologies. The authors formulate the problem as a stochastic dynamic program with a fairness (fill rate) constraint and exploit Blackwell's approachability theorem and Fenchel duality to characterize the attainable service level of each o-d pair. They use these insights to develop online policies that can enable more passengers boarding a train (efficiency) as well as ensure equitable service level (fairness) provided to each o-d pair. Numerical experiments on a set of transit data from Beijing show that this approach performs well compared with existing benchmarks in the literature.
{"title":"Online Passenger Flow Control in Metro Lines","authors":"Jinpeng Liang, Guodong Lyu, C. Teo, Ziyou Gao","doi":"10.1287/opre.2022.2417","DOIUrl":"https://doi.org/10.1287/opre.2022.2417","url":null,"abstract":"Crowds management during peak commuting hours is a key challenge facing metro systems worldwide, which results in serious safety concerns and unfair public transit service for commuters on different origin-destination (o-d) pairs. In “Online Passenger Flow Control in Metro Lines,” the authors investigate the impact of online decision making on the value of passenger flow control solution methodologies. The authors formulate the problem as a stochastic dynamic program with a fairness (fill rate) constraint and exploit Blackwell's approachability theorem and Fenchel duality to characterize the attainable service level of each o-d pair. They use these insights to develop online policies that can enable more passengers boarding a train (efficiency) as well as ensure equitable service level (fairness) provided to each o-d pair. Numerical experiments on a set of transit data from Beijing show that this approach performs well compared with existing benchmarks in the literature.","PeriodicalId":19546,"journal":{"name":"Oper. Res.","volume":"46 1","pages":"768-775"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75029262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Convex Reformulation and an Outer Approximation for a Large Class of Binary Quadratic Programs","authors":"Borzou Rostami, F. Errico, Andrea Lodi","doi":"10.1287/opre.2021.2241","DOIUrl":"https://doi.org/10.1287/opre.2021.2241","url":null,"abstract":"","PeriodicalId":19546,"journal":{"name":"Oper. Res.","volume":"24 1","pages":"471-486"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78114887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bastien Baldacci, Iuliia Manziuk, Thibaut Mastrolia, M. Rosenbaum
A Stackelberg actor–critic approach to optimal market making and incentives design with dark pools. We consider the issue of a market maker acting at the same time in the lit and dark pools of an exchange. The exchange wishes to establish a suitable make–take fee policy to attract transactions on its venues. We first solve the stochastic control problem of the market maker without the intervention of the exchange. Then, we derive the equations defining the optimal contract to be set between the market maker and the exchange. This contract depends on the trading flows generated by the market maker’s activity on the two venues. In both cases, we show existence and uniqueness, in the viscosity sense, of the solutions of the Hamilton–Jacobi–Bellman equations associated to the market maker and exchange’s problems. We finally design an actor–critic algorithm inspired by deep reinforcement learning methods, enabling us to approximate efficiently the optimal controls of the market maker and the optimal incentives to be provided by the exchange.
{"title":"Market Making and Incentives Design in the Presence of a Dark Pool: A Stackelberg Actor-Critic Approach","authors":"Bastien Baldacci, Iuliia Manziuk, Thibaut Mastrolia, M. Rosenbaum","doi":"10.1287/opre.2022.2406","DOIUrl":"https://doi.org/10.1287/opre.2022.2406","url":null,"abstract":"A Stackelberg actor–critic approach to optimal market making and incentives design with dark pools. We consider the issue of a market maker acting at the same time in the lit and dark pools of an exchange. The exchange wishes to establish a suitable make–take fee policy to attract transactions on its venues. We first solve the stochastic control problem of the market maker without the intervention of the exchange. Then, we derive the equations defining the optimal contract to be set between the market maker and the exchange. This contract depends on the trading flows generated by the market maker’s activity on the two venues. In both cases, we show existence and uniqueness, in the viscosity sense, of the solutions of the Hamilton–Jacobi–Bellman equations associated to the market maker and exchange’s problems. We finally design an actor–critic algorithm inspired by deep reinforcement learning methods, enabling us to approximate efficiently the optimal controls of the market maker and the optimal incentives to be provided by the exchange.","PeriodicalId":19546,"journal":{"name":"Oper. Res.","volume":"269 1","pages":"727-749"},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76752617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zheng Cui, Daniel Zhuoyu Long, Jin Qi, Lianmin Zhang
In the inventory routing problem, the supplier acts as a central decision maker who determines the replenishment quantities and also, the delivery times and routes to all retailers. In “Inventory Routing Problem Under Uncertainty”, Cui et al. develop a novel framework for the uncertain inventory routing problem and allow ambiguity in the probability distribution of each retailer's uncertain demand. Adopting a service-level viewpoint, they minimize the risk of uncertain inventory levels violating a prespecified acceptable range. They quantify that risk using a new decision criterion, the service violation index, that accounts for how often and how severely the inventory requirement is violated. The solutions proposed here are adaptive in the sense that they vary with the realization of uncertain demand. They provide algorithms to solve the problem exactly and then, demonstrate the superiority of their solutions by comparing them with several benchmarks.
{"title":"The Inventory Routing Problem Under Uncertainty","authors":"Zheng Cui, Daniel Zhuoyu Long, Jin Qi, Lianmin Zhang","doi":"10.1287/opre.2022.2407","DOIUrl":"https://doi.org/10.1287/opre.2022.2407","url":null,"abstract":"In the inventory routing problem, the supplier acts as a central decision maker who determines the replenishment quantities and also, the delivery times and routes to all retailers. In “Inventory Routing Problem Under Uncertainty”, Cui et al. develop a novel framework for the uncertain inventory routing problem and allow ambiguity in the probability distribution of each retailer's uncertain demand. Adopting a service-level viewpoint, they minimize the risk of uncertain inventory levels violating a prespecified acceptable range. They quantify that risk using a new decision criterion, the service violation index, that accounts for how often and how severely the inventory requirement is violated. The solutions proposed here are adaptive in the sense that they vary with the realization of uncertain demand. They provide algorithms to solve the problem exactly and then, demonstrate the superiority of their solutions by comparing them with several benchmarks.","PeriodicalId":19546,"journal":{"name":"Oper. Res.","volume":"1 1","pages":"378-395"},"PeriodicalIF":0.0,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73344230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A new study by Ata and Barjesteh proposes an effective joint dynamic pricing, outsourcing, and scheduling policy for a multiclass make-to-stock manufacturing system. The authors approximate this control problem with a Brownian control problem. They solve the Brownian problem explicitly by exploiting the solution to a Riccati equation and propose a policy for the manufacturing system based on its solution. The proposed policy is a two-sided barrier policy. Outsourcing and idling processes are used to maintain the workload above the lower and below the upper barriers, respectively. Dynamic prices are used to control the workload process between the two barriers. The authors show using a simulation study that the optimality gap of the proposed policy is small, and their proposed policy outperforms a long list of static pricing policies. Moreover, the gap between their proposed policy and the static pricing policies increases with the server utilization and the outsourcing cost.
{"title":"An Approximate Analysis of Dynamic Pricing, Outsourcing, and Scheduling Policies for a Multiclass Make-to-Stock Queue in the Heavy Traffic Regime","authors":"B. Ata, Nasser Barjesteh","doi":"10.1287/opre.2022.2361","DOIUrl":"https://doi.org/10.1287/opre.2022.2361","url":null,"abstract":"A new study by Ata and Barjesteh proposes an effective joint dynamic pricing, outsourcing, and scheduling policy for a multiclass make-to-stock manufacturing system. The authors approximate this control problem with a Brownian control problem. They solve the Brownian problem explicitly by exploiting the solution to a Riccati equation and propose a policy for the manufacturing system based on its solution. The proposed policy is a two-sided barrier policy. Outsourcing and idling processes are used to maintain the workload above the lower and below the upper barriers, respectively. Dynamic prices are used to control the workload process between the two barriers. The authors show using a simulation study that the optimality gap of the proposed policy is small, and their proposed policy outperforms a long list of static pricing policies. Moreover, the gap between their proposed policy and the static pricing policies increases with the server utilization and the outsourcing cost.","PeriodicalId":19546,"journal":{"name":"Oper. Res.","volume":"227 1","pages":"341-357"},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89189732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Assortment Personalization in E-commerce In the age of big data, online businesses have access to a tremendous amount of browsing and purchasing data from their customers. Consequently, there has been great effort in exploiting this data to offer personalized product assortments to each customer based on what is known about her or his preferences. A personalized assortment can potentially allow enhancing the customer experience as well as improving the revenue of the retailer. In “Joint Assortment Optimization And Customization Under A Mixture Of Multinomial Logit Models: On The Value Of Personalized Assortments,” Omar El Housni and Huseyin Topaloglu consider an optimization model that jointly optimizes the assortment of products carried by an online retailer as well as the personalized assortments offered to each customer. They study the value of personalization and develop algorithms with provable theoretical guarantees to solve the optimization problem.
在大数据时代，在线企业可以从客户那里获得大量的浏览和购买数据。因此，在利用这些数据为每个客户提供个性化的产品分类方面已经付出了巨大的努力，这些产品分类是基于对客户偏好的了解。个性化的分类可以潜在地增强客户体验，并提高零售商的收入。在“多项Logit模型混合下的联合分类优化和定制:关于个性化分类的价值”中，Omar El Housni和Huseyin Topaloglu考虑了一个优化模型，该模型可以共同优化在线零售商所携带的产品分类以及提供给每个客户的个性化分类。他们研究个性化的价值，并开发具有可证明的理论保证的算法来解决优化问题。
{"title":"Joint Assortment Optimization and Customization Under a Mixture of Multinomial Logit Models: On the Value of Personalized Assortments","authors":"Omar El Housni, Huseyin Topaloglu","doi":"10.1287/opre.2022.2384","DOIUrl":"https://doi.org/10.1287/opre.2022.2384","url":null,"abstract":"Assortment Personalization in E-commerce In the age of big data, online businesses have access to a tremendous amount of browsing and purchasing data from their customers. Consequently, there has been great effort in exploiting this data to offer personalized product assortments to each customer based on what is known about her or his preferences. A personalized assortment can potentially allow enhancing the customer experience as well as improving the revenue of the retailer. In “Joint Assortment Optimization And Customization Under A Mixture Of Multinomial Logit Models: On The Value Of Personalized Assortments,” Omar El Housni and Huseyin Topaloglu consider an optimization model that jointly optimizes the assortment of products carried by an online retailer as well as the personalized assortments offered to each customer. They study the value of personalization and develop algorithms with provable theoretical guarantees to solve the optimization problem.","PeriodicalId":19546,"journal":{"name":"Oper. Res.","volume":"13 1","pages":"1197-1215"},"PeriodicalIF":0.0,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84289576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Explaining and Resolving Delays in Projects Project management is responsible for 30% of the world’s economic activity, with an annual value of $27 trillion. Yet, despite half a century of research and the training of millions of project managers, many projects are delivered late. This is typically attributed to Parkinson’s Law, meaning the expansion of work to fill available time. However, in “Work More Tomorrow: Resolving Present Bias in Project Management,” Shi, Hall, and Cui identify and demonstrate the alternative explanation of time-inconsistent behavior, that is, present bias. Under present bias, a decision maker values immediate costs and rewards more than future ones. The authors show that this behavioral issue is responsible for procrastination by project workers and overall project delay. Borrowing concepts from popular employee savings schemes, they develop an incentive scheme that mitigates present bias and significantly enhances project performance, as measured by on-time frequency and expected project tardiness.
{"title":"Work More Tomorrow: Resolving Present Bias in Project Management","authors":"Yun Shi, Nicholas G. Hall, Xiangyu Cui","doi":"10.1287/opre.2022.2379","DOIUrl":"https://doi.org/10.1287/opre.2022.2379","url":null,"abstract":"Explaining and Resolving Delays in Projects Project management is responsible for 30% of the world’s economic activity, with an annual value of $27 trillion. Yet, despite half a century of research and the training of millions of project managers, many projects are delivered late. This is typically attributed to Parkinson’s Law, meaning the expansion of work to fill available time. However, in “Work More Tomorrow: Resolving Present Bias in Project Management,” Shi, Hall, and Cui identify and demonstrate the alternative explanation of time-inconsistent behavior, that is, present bias. Under present bias, a decision maker values immediate costs and rewards more than future ones. The authors show that this behavioral issue is responsible for procrastination by project workers and overall project delay. Borrowing concepts from popular employee savings schemes, they develop an incentive scheme that mitigates present bias and significantly enhances project performance, as measured by on-time frequency and expected project tardiness.","PeriodicalId":19546,"journal":{"name":"Oper. Res.","volume":"25 1","pages":"314-340"},"PeriodicalIF":0.0,"publicationDate":"2022-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89422474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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