Practice Of Operations Research Research Articles

Introduction: 2022 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research

The judges for the 2022 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research selected the four finalist papers featured in this special issue of the INFORMS Journal on Applied Analytics (IJAA). The prestigious Wagner Prize—awarded for achievement in implemented operations research, management science, and advanced analytics—emphasizes the quality and originality of mathematical models along with clarity of written and oral exposition. This year’s winning application describes the design and deployment of a generalized synthetic control, a powerful and innovative statistical method for identifying, in a noisy environment, retailing innovations that produce a small percentage improvement in a large volume of sales for Anheuser Busch Inbev. The remaining three papers describe an inverse control approach to allocating lung transplants that best meets targeted outcomes and has been implemented as the national lung allocation policy on March 9, 2023, across the United States; a human-centric, optimized parcel delivery system developed for Deutsche Post that saves money while meeting constraints learned dynamically from driver behavior; and an AI-based system developed for Alibaba that learns supplier behavior to improve replenishment ordering and inventory control. Supplemental Material: Full presentation videos with slides are available in the INFORMS Video Library at https://www.informs.org/Resource-Center/Video-Library and as electronic companions to the INFORMS Journal on Applied Analytics articles.

Generalized Synthetic Control for TestOps at ABI: Models, Algorithms, and Infrastructure

We describe a novel optimization-based approach—generalized synthetic control (GSC)—in which we learn from experiments conducted in a physical retail environment. GSC solves a long-standing problem of learning from experiments conducted in this environment when treatment effects are small, the environment is extremely noisy and nonstationary, and interference and adherence problems are commonplace. The utilization of GSC has demonstrated a remarkable increase in statistical power, approximately one hundredfold (100×) higher than conventional inferential methods. This innovative approach forms the basis of TestOps, a pioneering large-scale experimentation platform designed specifically for physical retailers. TestOps was developed and has been broadly implemented as part of a collaboration between Anheuser Busch Inbev (ABI) and a team of operations researchers and data engineers from the Massachusetts Institute of Technology. TestOps currently runs physical experiments impacting approximately 135 million USD in revenue every month and routinely identifies innovations that result in a 1%–2% increase in sales volume. The vast majority of these innovations would have remained unidentified had we not developed our novel approach to inference. Prior to our implementation, statistically significant conclusions could be drawn on only ∼6% of all experiments, a fraction that has now increased by 10-fold. Given its success, TestOps is being rolled out globally at ABI, driving significant revenue growth and enabling the extraction of valuable insights from large-scale physical experiments. History: This paper has been accepted for the INFORMS Journal on Applied Analytics Special Issue—2022 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research.

Human-Centric Parcel Delivery at Deutsche Post with Operations Research and Machine Learning

Features such as estimated delivery time windows and live tracking of shipments play a key role in improving the customer experience in last-mile delivery. The building blocks for enabling these features are reliable knowledge about the expected order of deliveries in a tour and precise delivery time window predictions. For Deutsche Post’s parcel delivery service in Germany, we developed a courier-centric routing algorithm and a corresponding state-of-the-art machine learning model for delivery time window predictions. The routing algorithm combines operations research with statistics and machine learning to implicitly gather and use the tacit knowledge of our experienced couriers within the tour generation. This is achieved by deducing and selecting appropriate precedence constraints from historical delivery data. This novel combination of optimization with data-driven constraints enabled us to provide custom routes to the individual couriers. It proved to be a main driver allowing us to provide accurate delivery time window predictions and live tracking of shipments. Our solution is used by Deutsche Post to plan the daily routes of couriers to the approximately 13,000 parcel delivery districts in Germany as well as to provide live tracking and estimated delivery time windows for 1.6 million parcels each day. History: This paper has been accepted for the INFORMS Journal on Applied Analytics Special Issue—2022 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research.

AI vs. Human Buyers: A Study of Alibaba’s Inventory Replenishment System

Inventory management is one of the most important components of Alibaba’s business. Traditionally, human buyers make replenishment decisions: although artificial intelligence (AI) algorithms make recommendations, human buyers can choose to ignore these recommendations and make their own decisions. The company has been exploring a new replenishment system in which algorithmic recommendations are final. The algorithms combine state-of-the-art deep reinforcement learning techniques with the framework of fictitious play. By learning the supplier’s behavior, we are able to address the important issues of lead time and fill rate on order quantity, which have been ignored in the extant literature of stochastic inventory control. We present evidence that our algorithms outperform human buyers in terms of reducing out-of-stock rates and inventory levels. More interestingly, we have seen additional benefits amid the pandemic. Over the last two years, cities in China partially and intermittently locked down to mitigate COVID-19 outbreaks. We have observed panic buying from human buyers during lockdowns, leading to the bullwhip effect. By contrast, panic buying and the bullwhip effect can be mitigated using our algorithms due to their ability to recognize changes in the supplier’s behavior during lockdowns. History: This paper has been accepted for the INFORMS Journal on Applied Analytics Special Issue—2022 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research.

Applying Analytics to Design Lung Transplant Allocation Policy

In 2019, the United Network for Sharing (UNOS), which has been operating the Organ Procurement and Transplantation Network (OPTN) in the United States since 1984, was seeking to design a new national lung transplant allocation policy. The goal was to develop a point system that would prioritize candidates on the waiting list in a way that would yield more efficient and equitable outcomes. Our joint Massachusetts Institute of Technology (MIT)/UNOS team joined forces with the OPTN Lung Transplantation Committee in these policy design efforts. We discuss how our team applied a novel analytical framework, which was developed at MIT and utilizes optimization, regression, and simulation techniques, to illuminate salient trade-offs among outcomes and guide the choice of how to weigh different point attributes in the allocation formula. The committee selected for the allocation formula weights that were highlighted in the team’s analysis. The team’s proposal was implemented as the national lung allocation policy on March 9, 2023 across the United States. History: This paper has been accepted for the INFORMS Journal on Applied Analytics Special Issue—2022 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research.

Is there an ethical operational research practice? And what this implies for our research?

The ethical dimension of Operational Research and Decision Aiding, although not a new subject, has become more of a concern, both for the large public and the OR community, because of the wide spread of autonomous artefacts endowed with decision capacity thanks to the use of models, methods and tools developed within our field. The paper addresses the question of whether there exists an “Ethical Operational Research practice”, identifies the ethical questions which are specific to our professional community and suggests research topics which, although independently developed, are relevant for handling such questions.

Introduction: 2021 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research

The judges for the 2021 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research selected the five finalist papers featured in this special issue of the INFORMS Journal on Applied Analytics. The prestigious Wagner Prize—awarded for achievement in implemented operations research, management science, and advanced analytics—emphasizes the quality and originality of mathematical models along with clarity of written and oral exposition. This year’s winning application describes the design and deployment of Eva, the Greek COVID-19 testing system used as Greece was opening up for tourism in 2020. The remaining four papers describe the stochastic modeling and mixed-integer programming system used to optimize the Atlanta police patrol zones for better police balance and reduced response time to emergency calls; Lyft’s new priority dispatch system, which solves the ride-sharing productivity paradox whereby increases in efficiency do not benefit the drivers; the application of advanced analytics to assist local and federal law enforcement organizations in their efforts to disrupt sex-trafficking networks; and the development of a new after-sales service concept, which increases chip availability for ASML’s customers.

Introduction: 2020 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research

The judges for the 2020 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research selected the five finalist papers featured in this special issue of the INFORMS Journal on Applied Analytics (IJAA). The prestigious Wagner Prize—awarded for achievement in implemented operations research, management science, and advanced analytics—emphasizes the quality and originality of mathematical models along with clarity of written and oral exposition. This year’s winning application is a system for optimally managing Dow Agrosciences’ (now Corteva) seed corn portfolio, which includes seeds for several hundred varieties of corn and is valued at more than $1 billion. The model employs Bayesian analytic methods to estimate crop yields from expert judgement. Stochastic optimization is then used to determine backup production in South America while dealing with yield uncertainty in North America. The remaining four papers include an efficient mixed-integer program used by Birchbox to determine individualized subscriber product sets; a scheduling system for Argentina’s premier soccer league; an incentive system for encouraging Lyft drivers to reposition to provide improved service; and a system for optimizing the electric bus network design in Rotterdam.

Editorial: The 13th Rothkopf Rankings: All-Time Interfaces/INFORMS Journal on Applied Analytics 50-Year Anniversary Special Edition

In 1996, Michael Rothkopf created an index of institutional contributions to the practice of operations research (OR) and management science (MS). Since then, Ron Fricker and I have continued to calculate, evolve, and extend this ranking. In this Interfaces (INT) and INFORMS Journal on Applied Analytics (IJAA) anniversary ranking, I analyze organizational contributions to the practice of OR/MS in INT since the inception of the journal in 1971. I calculate all three prior ranking measures—visibility, yield, and academic yield—and a blend of the rankings. This analysis considers only articles in INT/IJAA, which is a departure from prior rankings, which included applied work in some other journals. However, for the first time, we have a single database of every article ever published in INT/IJAA, allowing analysis of trends over time. I am also able to compute the all-time contributions of nonacademic institutions as done by Fricker in 2012.

Pragmatism in professional practice

AbstractIn recent years, there has been a resurgence of interest in the American philosophy of pragmatism. The paper reviews the application of pragmatisms in five selected areas of professional practice: technology, law, politics, medical and social work, and education. Each area is examined for evidence that the ideas of pragmatism have been taken up academically in the research literature. The literature is then examined for evidence that the academic work has permeated the actions of professionals. Each of the chosen practice areas is clearly dominated by pragmatic, instrumental activities. Despite this and a good deal of discussion in the academic literature, there is only limited evidence that professionals, in so far as they exhibit pragmatist behaviour, make any explicit connection with the philosophy of pragmatism. The early pragmatists argued that pragmatic behaviour arises from man's need to solve problems quickly, using his limited understanding of the situation, in order to survive and flourish: no philosophy had been required to guide such behaviour. Today, philosophy is often consulted on questions of ethical and moral dilemmas in most practice areas, but the philosophy of pragmatism may well not feature in such discussions. Experience in operational research (OR) practice is reviewed and compared with that in the five other practice areas. From the reviews, a list of the habits and orientations is synthesized, habits and orientations that could be taken to characterize pragmatism in professional practice.

A New Scatter Search Design for Multiobjective Combinatorial Optimization with an Application to Facility Location

Metaheuristic optimization is at the heart of the intersection between computer science and operations research. The INFORMS Journal of Computing has been fundamental in advancing the ideas behind metaheuristic methodologies. Fred Glover’s “Tabu Search—Part I” was published more than 30 years ago in the first volume of the then ORSA Journal on Computing. This article, one of the most cited in the area of heuristic optimization, paved the way for many contributions to the methodology and practice of operations research. As a continuation of this stream of research, we describe a new scatter search design for multiobjective optimization. The design includes a short-term memory tabu search and a path relinking combination method. We show how the strategies and mechanisms within scatter search and tabu search can be combined to produce a highly effective approach to multiobjective optimization.

Introduction: 2019 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research

Competition for the 2019 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research provided the five finalist papers featured in this special issue of the INFORMS Journal on Applied Analytics (IJAA). The prestigious Wagner Prize—awarded for achievement in implemented operations research, management science, and advanced analytics—emphasizes quality and originality of mathematical models and clarity of written and oral exposition. This year’s winning application is a ride-dispatching solution that the Chinese ride service DiDi developed to match ride requests to available drivers. The model uses a Markov decision process along with machine learning to optimize the assignments, resulting in improved response rates, fulfillment rates, and driver income. The remaining papers include an optimization model that generates daily tutoring schedules for students and teachers at Hopeful Journeys, a school for children with disabilities; integer programming models to develop bus-route assignments for the Denver Public Schools; a novel pricing methodology, in the context of limited historical data, for reusable spare parts; and a machine learning approach to improve airline passenger flows through London’s Heathrow airport.

Artefact appropriation in facilitated modelling: An adaptive structuration theory approach

Scholars have long acknowledged the importance of unveiling the black box of Operational Research (OR) practice. However, despite the emerging empirical studies in the area known as “Behavioural OR”, there is still a dearth of research into how artefacts are used at the micro-level of OR practice. This article addresses this gap by using adaptive structuration theory (AST) to study the appropriation (use) of artefacts during a facilitated modelling (FM) workshop. We argue that the appropriation of artefacts from the workshop participants enables them to engage in negotiation of meaning with action implications effectively, but appropriation occurs at varying intensities (high, medium, and low) depending on the issue of concern. Moreover, we identify that artefacts are reproduced if their reproduction is an aim or part of an aim of strategic discourse. Finally, we outline the limitations of our study and future research avenues.

О ВЕРОЯТНОСТНОМ ОПРЕДЕЛЕНИИ НАДЕЖНОСТИ ОБЪЕКТА ТЕХНОСФЕРЫ ПРИ ОПАСНЫХ ВОЗДЕЙСТВИЯХ

The subject of research is the process associated with determining the reliability parameter of buildings (structures) for their further operation in the technological process, causing effects in the form of additional loads (explosions, fires, vibration processes). The solution of such problems is relevant for the buildings (structures) acquired (rented) by the owner for further operation in the production process, in the technology of which fire and explosion hazardous substances (materials) are handled, stored or processed. The purpose of the study is to develop an approach that allows one to determine the parameter of the reliability of a building (structure) for operation under additional loads. To determine the indicators of safe permissible states of buildings (structures), the use of various criterion characteristics included in the content of deterministic, statistical and probabilistic approaches is given. A feature of assessing the reliability of buildings (structures) for their operation under additional loads (explosions, fires, vibration processes) is to determine the indicator of a given margin of safety and its stability under possible realized impacts. To solve the problem, it is proposed to use a simplified assessment of the safety margin of a building (structure) in terms of yield strength (for steel elements) and strength (for base materials, load-bearing walls, partitions and ceilings) corresponding to the maximum permissible values for their destruction. A consistent theoretical description of the formulas is presented, which makes it possible to establish a relationship between the safety margin of a building (structure) and the probability of its destruction under the implemented influences. An innovative approach is described that allows solving problems of assessing the strength reliability of structural elements of buildings (structures), when it is important to obtain guaranteed characteristics of an indicator of a given safety margin, its resistance to possible realized influences (explosions, fires, vibration processes). The use of the material in order to determine the reliability indicators based on risks allows us to consider the calculated values of the safety margin of a building (structure), which meets the established requirements for assessing efficiency from the point of view of the theory and practice of operations research.

On the probability determination of the reliability of a technosphere object under hazardous influence

The use of various criteria characteristics included in the content of deterministic, statistical and probabilistic approaches is shown in this article for determination the indicators of safe permissible conditions of buildings (structures). A feature of assessing the reliability of buildings (structures) for their operation under additional loads (explosions, fires, vibration processes) is the determination of an indicator of a given safety margin and its stability under possible realized effects. The aim of the study is to develop an approach to determine the reliability indicator of a building (structure), for operation in conditions of additional loads. The subject of the study is the process associated with the determination of the reliability indicator of buildings (structures), for their further operation in the technological process, causing effects in the form of additional loads (explosions, fires, vibration processes). The solution to such problems is relevant for buildings (structures) that are acquired (leased) by the owner, for their further operation in the production process, in the technology of which fire and explosion hazardous substances (materials) are handled, stored or processed. To solve the tasks, it is proposed to use a simplified assessment of the safety margin of a building (structure) by yield strengths (for steel elements) and strength (for base materials, load-bearing walls, partitions and ceilings) corresponding to the maximum allowable values for their destruction. The article provides a consistent theoretical description of the formulas, which allows us to establish a relationship between the safety margin of a building (structure) and the probability of its destruction during realized impacts. An innovative approach is described that allows us to solve the problems of assessing the strength reliability of structural elements of buildings (structures), when it is important to be able to obtain guaranteed characteristics of a given safety factor, its resistance to possible realized impacts - explosions, fires, vibration processes. The use of the material, in order to determine reliability indicators based on risks, allows us to consider the calculated values of the safety margin of a building (structure), which meets the established requirements for evaluating effectiveness from the point of view of theory and practice of operations research.

On justifying the norms underlying decision support

When decision sciences are applied to concrete problems, Decision Makers (DM), concerned stakeholders, and the general public typically expect clear recommendations. As emphasized in particular in the literature on ethical dimensions of Operational Research (OR) practice, such recommendations are unavoidably conditioned by norms or normative conceptions. Although an extensive literature is devoted to promoting certain norms designed to be largely accepted by decision analysts, studies specifically devoted to determine, at a general level, how decision analysts can decide which norms should underlie their work, are found lacking. To make up for this lacuna, we flesh out the concept of justification. We develop requirements that any justification should satisfy to qualify for being able to justify norms on which recommendations can rest. We then introduce and recommend a series of practical rules that decision analysts should abide by, on the basis of which, in a given decision situation, a decision analyst can decide, together with the DM, whether a given norm underlying a given recommendation can be adopted.

Stakeholder identification and engagement in problem structuring interventions

This paper addresses the under-researched issue of stakeholder identification and engagement in problem structuring interventions. A concise framework is proposed to aid critical reflection in the design and reporting of stakeholder identification and engagement. This is grounded in a critical-systemic epistemology, and is informed by social identity theory. We illustrate the utility of the framework with an example of a problem structuring workshop, which was part of a green innovation project on the development of a technology for the recovery of rare metals from steel slag. The workshop was initially going to be designed to surface stakeholder views on the technology itself. However, it became apparent that a range of other strategic issues concerning the future of the site were going to impact on decision making about the use of steel slag. It therefore became important to evolve the agenda for the problem structuring, and this is where the critical-systemic approach made a difference. It enabled the workshop to be reframed as a community-based event looking at how the former steelworks site could be developed for new purposes. Evaluation of this problem structuring intervention revealed significant stakeholder learning about the issues needing to be accounted for, and a range of possible options for the development of the steelworks site were explored. The paper ends with a discussion of the utility of social identity theory for understanding the processes and outcomes of the workshop, and reflections are provided on its implications for operational research practice more generally.

Introduction: 2018 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research

Competition for the 2018 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research provided the six finalist papers featured in this special issue of the INFORMS Journal on Applied Analytics (IJAA). The prestigious Wagner Prize—awarded for achievement in implemented operations research, management science, and advanced analytics—emphasizes quality and originality of mathematical models and clarity of written and oral exposition. If you have ever rented a bike from Motivate, the largest provider of bike-sharing systems in the United States, you have benefited from the analytical work done by the winning team from Cornell University, which improves the allocation of docks to stations and created the Bike Angels program, an incentive scheme to crowdsource rebalancing, thus improving bike availability in San Francisco and New York City. The remaining papers describe work on developing a first-of-a-kind market design for the reallocation of fishing shares in South Wales, using primal-dual algorithms for omni-channel retail fulfillment, improving the seat-allocation process for admissions to engineering colleges in India, using structured and unstructured data in predictive modeling for repairing malfunctioning appliances, and rescuing missing tourists in nature reserves in China.

Making OR practice visible: Using ethnomethodology to analyse facilitated modelling workshops

Empirical studies attempting to open the ‘black box’ of the practice of operational research (OR) are beginning to appear in the literature, particularly within the area known as behavioural OR. Many scholars within this community share a commitment to both empirically investigate what OR practitioners and users actually do when engaged in OR-supported processes, and evaluate what the effect of these ‘doings’ is. Despite these developments, we still know very little about the complexities and situated specifics of OR practice as it happens on the ground. This is mostly due to the methodological challenges involved in treating real-time OR practice as an analytical problem, which requires making OR practice ‘visible’ by bringing to the fore its material and interactional features for close examination. In this paper we adopt ethnomethodology as one way to address this challenge. Using an empirical vignette drawn from a facilitated modelling workshop in which causal mapping was used with a top management team, we illustrate how an ethnomethodologically-informed perspective can reveal the ways in which OR-supported activity is practically accomplished by those involved, moment by moment, and with what effects. We conclude the paper by summarising the contribution that these kinds of fine-grained studies of OR practice make to the behavioural OR agenda, and outline some potentially useful avenues for future research.

Introduction: 2016 Franz Edelman Award for Achievement in Operations Research and the Management Sciences

This special issue of Interfaces is devoted to the finalists of the 45th annual competition for the Franz Edelman Award for Achievement in Operations Research and the Management Sciences, the profession’s prestigious award for the practice of operations research and business analytics. As in previous years, the six finalists this year cover a wide range of industries and functions.