INFORMS J. Appl. Anal.最新文献_第5页

Using Machine Learning to Improve Public Reporting on U.S. Government Contracts 利用机器学习改进美国政府合同的公开报告

INFORMS J. Appl. Anal. Pub Date : 2021-08-17 DOI: 10.1287/lytx.2021.04.23n

William A. Muir, Daniel Reich

{"title":"Using Machine Learning to Improve Public Reporting on U.S. Government Contracts","authors":"William A. Muir, Daniel Reich","doi":"10.1287/lytx.2021.04.23n","DOIUrl":"https://doi.org/10.1287/lytx.2021.04.23n","url":null,"abstract":"The U.S. government procures more than $500 billion annually in goods and services on public contracts, which it classifies using a hierarchical product and service taxonomy. Classification serves several purposes, including transparency in the use of taxpayer funding; reporting, tracing, and segmenting government expenditures; budgeting; and forecasting. Government acquisition personnel have historically performed these classifications manually, resulting in a process that is time-consuming and error-prone and offers limited visibility into government purchases. The problem faced is not unique to the public sector and is common across retail, manufacturing, and healthcare, among other settings. Using almost 4 million historical data records on governmental purchases, we fit a series of classifiers and demonstrate (a) superior performance when explicitly modeling the hierarchical structure of information domains through the use of top-down strategies and (b) the effectiveness of character-level convolutional neural networks when textual inputs are terse and contain irregularities such as abnormal character combinations and misspellings, which are common in government contracts. Our machine learning models are embedded in multiple software applications, including a web application that we developed, used by federal government personnel and other contracting professionals.","PeriodicalId":430990,"journal":{"name":"INFORMS J. Appl. Anal.","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126650113","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}

引用次数: 2

Pricing Anomalies and Arbitrage in Container Transport in India 印度集装箱运输中的定价异常与套利

INFORMS J. Appl. Anal. Pub Date : 2021-07-26 DOI: 10.1287/inte.2021.1082

Amita Upadhyay

{"title":"Pricing Anomalies and Arbitrage in Container Transport in India","authors":"Amita Upadhyay","doi":"10.1287/inte.2021.1082","DOIUrl":"https://doi.org/10.1287/inte.2021.1082","url":null,"abstract":"Intermodal transportation requires multiple entities to manage diverse resources under complex regulations and contracts. In this paper, we carry out a multidisciplinary cross-functional analysis of container rail haulage pricing and operations in India. We discover that the total haulage cost of a container train unduly depends on the position of the containers within the train, which is referred to here as position arbitrage. The main objective of this paper is to introduce and analyze this new concept of arbitrage for the first time in the literature. We derive the limits to the arbitrage, present management insights and empirical results, and explain that the arbitrage is undesirable because of its adverse effects on the efficiency of the container supply chain. With a real case, we empirically show that container train operators can save an average of 450 million INR annually by exploiting the arbitrage. On completion of dedicated freight corridors, the annual total value of the arbitrage can increase by one billion Indian rupees. This research is also beneficial for the railways to understand the implications of haulage pricing on operational efficiency and also for the port operators and shippers to understand the implications of the arbitrage for their operations.","PeriodicalId":430990,"journal":{"name":"INFORMS J. Appl. Anal.","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116676650","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}

引用次数: 0

Developing Optimal Student Plans of Study 制定最佳学生学习计划

INFORMS J. Appl. Anal. Pub Date : 2021-07-22 DOI: 10.1287/INTE.2021.1083

R. Bowman

引用次数: 1

Portfolio-Wide Optimization of Pharmaceutical R&D Activities Using Mathematical Programming 基于数学规划的药品研发活动组合优化

INFORMS J. Appl. Anal. Pub Date : 2021-06-16 DOI: 10.1287/INTE.2021.1074

Hua Wang, J. Dieringer, Steve Guntz, Shankar Vaidyaraman, Shekhar Viswanath, Nikolaos H. Lappas, S. García-Muñoz, Chrysanthos E. Gounaris

{"title":"Portfolio-Wide Optimization of Pharmaceutical R&D Activities Using Mathematical Programming","authors":"Hua Wang, J. Dieringer, Steve Guntz, Shankar Vaidyaraman, Shekhar Viswanath, Nikolaos H. Lappas, S. García-Muñoz, Chrysanthos E. Gounaris","doi":"10.1287/INTE.2021.1074","DOIUrl":"https://doi.org/10.1287/INTE.2021.1074","url":null,"abstract":"The research and development (R&D) management in any major research pharmaceutical company is constantly faced with the need to make complicated activity scheduling and resource allocation decisions, as they carry out scientific work to develop new therapeutic products. This paper describes how we develop a decision support tool that allows practitioners to determine portfolio-wide optimal schedules in a systematic, quantitative, and largely automated fashion. Our tool is based on a novel mixed-integer linear optimization model that extends archetypal multimode resource-constrained project scheduling models in order to accommodate multiple rich features that are pertinent to the Chemistry, Manufacturing, and Controls (CMC) activities carried out within the pharmaceutical R&D setting. The tool addresses this problem at the operational level, determining schedules that are optimal in light of chosen business objectives under activity sequencing, resource availability, and deadline constraints. Applying the tool on current workload data demonstrates its tractability for practical adoption. We further illustrate how, by utilizing the tool under different input instances, one may conduct various tactical analyses to assess the system’s ability to cope with sudden changes or react to shifting management priorities.","PeriodicalId":430990,"journal":{"name":"INFORMS J. Appl. Anal.","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131095027","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}

引用次数: 2

Contextual Complications in Analytical Modeling: When the Problem is Not the Problem 分析建模中的情境复杂性:当问题不是问题时

INFORMS J. Appl. Anal. Pub Date : 2021-06-15 DOI: 10.1287/INTE.2021.1078

M. Gorman

{"title":"Contextual Complications in Analytical Modeling: When the Problem is Not the Problem","authors":"M. Gorman","doi":"10.1287/INTE.2021.1078","DOIUrl":"https://doi.org/10.1287/INTE.2021.1078","url":null,"abstract":"In this essay, I describe 10 critical complicating factors that directly affect the six basic modeling components of problem definition, assumptions, decision variables, objective functions, constraints, and solution approach. The proposed 10 contextual complicating factors are (1) organization, (2) decision-making processes, (3) measures and key performance indicators, (4) rational and irrational biases, (5) decision horizon and interval, (6) data availability, accuracy, fidelity, and latency, (7) legacy and other computer systems, (8) organizational and individual risk tolerance, (9) clarity of model and method, and (10) implementability and sustainability of the approach. I hypothesize that the core analytical problem cannot be adequately described or usefully solved without careful consideration of these factors. I describe detailed examples of these contextual factors’ effects on modeling from six published applied prescriptive analytics projects and provide other examples from the literature. The complicating factors are pervasive in these projects, directly and dramatically affecting basic modeling components over half the time. Further, in the presence of these factors, 23 statistically significant correlations tend to form in three clusters, which I characterize as culture, decision, and project clusters. Unrecognized, these factors would have hampered the implementation and ongoing use of these analytical models; in a sense, the models themselves were wrong, absent consideration of these contextual considerations. With these insights, I hope to help practitioners identify the effects of these common complications and avoid project failure by incorporating these contextual factors into their modeling considerations. Future research could seek to better understand these factors and their effects on modeling.","PeriodicalId":430990,"journal":{"name":"INFORMS J. Appl. Anal.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114621423","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}

引用次数: 3

Theory-Driven Practical Approach to Integrate R&D and Production Planning for Portfolio Management in Agribusiness 农业综合企业投资组合管理中研发与生产计划整合的理论驱动实践方法

INFORMS J. Appl. Anal. Pub Date : 2021-05-13 DOI: 10.1287/INTE.2021.1080

S. Bansal, G. Gutierrez, M. Nagarajan

{"title":"Theory-Driven Practical Approach to Integrate R&D and Production Planning for Portfolio Management in Agribusiness","authors":"S. Bansal, G. Gutierrez, M. Nagarajan","doi":"10.1287/INTE.2021.1080","DOIUrl":"https://doi.org/10.1287/INTE.2021.1080","url":null,"abstract":"Agribusiness firms, with an eye toward increasing population and evolving weather patterns, are investing heavily into developing new varieties of staple crops that can provide higher yields and are robust to weather fluctuations. In this paper, we describe a multiyear effort at Dow Agrosciences (now Corteva) to manage its seed corn portfolio, which includes several hundred seeds and is valued at more than $1 billion. The effort had two mutually interacting parts: (1) developing a decision-analytic theory to estimate the production yield distributions for new seed varieties from discrete quantile judgments provided by plant biology experts and (2) developing an optimization protocol to determine Dow's annual production plan for the seed portfolio with the flexibility of backup production in South America, under production yield uncertainty. The first part, owned by the research and development (R&D) function, provides yield probability distributions as inputs to the optimization protocol of the second part, which the production function owns. The results of the optimization problem, which include information about the attractiveness of specific future varieties, are returned to R&D. Both parts incorporate contextual details specific to this industry. In this paper, we show the optimality of linear policies for both problems. Additionally, the linear policies have many attractive structural properties that continue to hold for the more complex instances of the problems. A major strength of the theory we developed is that it is implementable in a transparent fashion, providing managers with a user-friendly, real-time decision support tool. The implementation of the theory developed has led to significant monetary and managerial benefits at Dow.","PeriodicalId":430990,"journal":{"name":"INFORMS J. Appl. Anal.","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128556917","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}

引用次数: 2

A Machine Learning-Based System for Predicting Service-Level Failures in Supply Chains 基于机器学习的供应链服务水平故障预测系统

INFORMS J. Appl. Anal. Pub Date : 2021-04-23 DOI: 10.1287/INTE.2020.1055

Gabrielle Gauthier Melançon, P. Grangier, Eric Prescott-Gagnon, Emmanuel Sabourin, Louis-Martin Rousseau

{"title":"A Machine Learning-Based System for Predicting Service-Level Failures in Supply Chains","authors":"Gabrielle Gauthier Melançon, P. Grangier, Eric Prescott-Gagnon, Emmanuel Sabourin, Louis-Martin Rousseau","doi":"10.1287/INTE.2020.1055","DOIUrl":"https://doi.org/10.1287/INTE.2020.1055","url":null,"abstract":"Despite advanced supply chain planning and execution systems, manufacturers and distributors tend to observe service levels below their targets, owing to different sources of uncertainty and risks. These risks, such as drastic changes in demand, machine failures, or systems not properly configured, can lead to planning or execution issues in the supply chain. It is too expensive to have planners continually track all situations at a granular level to ensure that no deviations or configuration problems occur. We present a machine learning system that predicts service-level failures a few weeks in advance and alerts the planners. The system includes a user interface that explains the alerts and helps to identify failure fixes. We conducted this research in cooperation with Michelin. Through experiments carried out over the course of four phases, we confirmed that machine learning can help predict service-level failures. In our last experiment, planners were able to use these predictions to make adjustments on tires for which failures were predicted, resulting in an improvement in the service level of 10 percentage points. Additionally, the system enabled planners to identify recurrent issues in their supply chain, such as safety-stock computation problems, impacting the overall supply chain efficiency. The proposed system showcases the importance of reducing the silos in supply chain management.","PeriodicalId":430990,"journal":{"name":"INFORMS J. Appl. Anal.","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122934700","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}

引用次数: 9

The Impact of Age Demographics on Interpreting and Applying Population-Wide Infection Fatality Rates for COVID-19 年龄人口统计学对COVID-19全人群感染病死率的解释和应用的影响

INFORMS J. Appl. Anal. Pub Date : 2021-04-20 DOI: 10.1287/INTE.2020.1070

M. MacLeod, D. Hunter

{"title":"The Impact of Age Demographics on Interpreting and Applying Population-Wide Infection Fatality Rates for COVID-19","authors":"M. MacLeod, D. Hunter","doi":"10.1287/INTE.2020.1070","DOIUrl":"https://doi.org/10.1287/INTE.2020.1070","url":null,"abstract":"The ongoing coronavirus disease 2019 (COVID-19) pandemic affects the Canadian Armed Forces (CAF) and its members in multiple ways. As the CAF manages its own healthcare system for its members, it must consider the impact of COVID-19 not only on the operational effectiveness of its workforce but also on its healthcare operations. Furthermore, given that the CAF has deployed task forces in support of other government departments, including into long-term care facilities that are experiencing outbreaks, it is important for the CAF to maintain situational awareness of the outbreak in the Canadian population generally. In providing analytical support to the CAF on these questions, we focused on establishing the applicability of estimates of COVID-19 infection fatality rates (IFRs) from the literature to the CAF and to the Canadian public. This paper explores how the age-dependent effects of COVID-19 must be taken into account when comparing estimates based on countries with very different age profiles, such as China and Italy. Furthermore, it explores how varying age structures within a country (e.g., within a subnational jurisdiction, or within a given working population) should affect how analysts apply estimates of IFR to scenarios involving those specific populations.","PeriodicalId":430990,"journal":{"name":"INFORMS J. Appl. Anal.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121360607","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}

引用次数: 4

Data-Driven Optimization for Atlanta Police-Zone Design 亚特兰大警区设计的数据驱动优化

INFORMS J. Appl. Anal. Pub Date : 2021-03-30 DOI: 10.1287/inte.2022.1122

Shixiang Zhu, He Wang, Yao Xie

引用次数: 2

Dynamic Inventory Allocation for Seasonal Merchandise at Dillard's 迪拉德公司季节性商品的动态库存分配

INFORMS J. Appl. Anal. Pub Date : 2021-03-18 DOI: 10.1287/INTE.2020.1068

Junxuan Li, A. Toriello, He Wang, S. Borin, Christina Gallarno

引用次数: 0