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As the INFORMS Journal on Applied Analytics (formerly Interfaces) reaches its 50th year, the current editor-in-chief (EiC) and each of the five former (surviving) EiCs recount the major events and developments of his tenure. Our objective is to trace the evolution of the journal and trends of the publication from its roots until today. The editorial closes with a discussion of the trends and likely future directions for the journal.

In this work, we discuss how analytics is evolving in industry and academia. To assess industry needs, we conducted a text-mining study of online job postings for analytics-related positions. We also conducted a survey of academic programs in analytics-related master’s programs to ascertain topic coverage relative to industry needs. Based on these two studies, we discuss gaps that we believe need to be addressed. While industry moves along the analytics maturity spectrum from descriptive to predictive to prescriptive optimization-based analytics, analytics master’s programs are focusing less on optimization and more heavily on predictive analytics, thus creating the future potential for a gap in the analytics training provided by academia and the future analytics needs of industry.

Data visualization is the process of visualizing data through tables, charts, graphs, maps, and other visual aids. Data visualization is often thought of as a descriptive tool, but it is also important for use in predictive and prescriptive analytics. It serves as a tool for descriptive data exploration, but also for communicating insights from data and from analytical models. In this tutorial, we provide a concise discussion of best practices for data visualization for effective communication.

In this paper, we present an exact method for the demand weighted vehicle routing problem. This problem arises when the objective is to minimize the distance traveled by the vehicles weighted by the number of passengers on the routes. The resulting model is a non-convex, mixed-integer quadratic program and we show how to reformulate this problem as a linear integer program with auxiliary variables. The reformulation provides very tight lower bounds on the optimal solution value and little enumeration is required. However, the reformulated model is very large and therefore, it is solved with a branch, price and cut algorithm. Using COIN-OR software, we provide computational results with actual data from a large urban university.

We conducted a survey of academically affiliated members of INFORMS to better understand the extent of the current usage of Interfaces. We asked respondents if and how they use Interfaces as a resource in teaching and research, and we also asked a series of questions about their careers and the institutions at which they are employed. Our results show that Interfaces is used mostly in teaching MBA core and elective courses and MS and PhD courses in operations research and operations management. Edelman papers are generally used mostly for teaching and reference in research. In this paper, we describe some differences based on type of academic institution and on whether the respondent is an Interfaces subscriber; we also identify opportunities for Interfaces.

Sometimes being suboptimal is best. Cuts to the unit hypercube, as Balas and Jeroslow discuss [Balas E, Jeroslow R (1972) Canonical cuts on the unit hypercube. SIAM J. Appl. Math. 23(1):61–69], provide a simple approach to generating alternative optima and (or) providing a family of suboptimal solutions for one’s clients to consider. In this paper, I discuss how to generate useful suboptimal solutions using Balas and Jeroslow’s cuts to the unit hypercube and why clients are willing to pay for them.

In his last months as editor in chief of this journal, the first author was seeking papers for this 40th anniversary issue of Interfaces. He wanted to generate a final issue with works from folks who were truly in the interface between academia and industry. In the first author’s opinion, few currently fit that bill better than the second author. When approached by the first author about a paper for this issue, the second author happily agreed. We then set about finding a topic that had not been broached. The first author has been consulting successfully for 20 years or so, but had never landed a project in which the client would agree to a percentage-of-savings fee. He had once come close with a Fortune 100 company. However, the client’s boss must have been scared off by the glee in the first author’s voice and never approved the deal. The second author has been able to accomplish percentageof-savings deals and has created a very successful company based on operations research (OR), while continuing to be a very productive professor. How has he been so successful in navigating the interface? That’s what the first author set out to learn and share with the readers of Interfaces. The most efficient approach for acquiring this information turned out to be an interview format. In what follows, the first author (JC) discusses, among other topics, monetizing the value created by OR with the second author (ST) in the hopes that we can all learn from the second author’s experiences. JC: OR methods, when applied appropriately, have created significant monetary and economic value. Most of the time, however, it appears that the OR person who played a role in this value creation does not get a proportional amount in compensation. In your OR Practice paper published earlier this year (Tardif et al. 2010), you discuss a project at Deere executed under a gain-sharing agreement. Can you give some details? ST: I agree with your general observation. The short answer to your question on the Deere project is that it was a 50-50 split based on the value created that can be attributed to this OR effort. In the paper, we show that the value created is clearly incremental over what Deere would have made (or was making from parallel projects, termed as “preexisting” initiatives) had we not done the engagement. Thus, we were paid about $5 million for this project over a period of 2 2 years. As you said, typically, even if an OR project saves $500 million and wins the Edelman competition (or is a competition finalist), the OR folks on that team most likely make less than $5 million. JC: Let’s take a step back. How did you get to this gain-sharing agreement? ST: This was not our first interaction with Deere. When we were crafting this arrangement during the fall of 2004, we had already done two very successful OR-based projects. One was an Edelman finalist in 2004 (Troyer et al. 2005); as a result of this project, Deere either eliminated or avoided over $1 billion of inventory. In the second project, we helped Deere save tens of millions of dollars by optimizing its product portfolio (Yunes et al. 2007).

Expanding human population and economic growth have led to large-scale conversion of natural habitat to human-dominated landscapes with consequent large-scale declines in biodiversity. Conserving biodiversity, while at the same time meeting expanding human needs, is an issue of utmost importance. In this paper we develop a spatially explicit landscape-level model for analyzing the biological and economic consequences of alternative land-use patterns. The spatially explicit biological model incorporates habitat preferences, area requirements and dispersal ability between habitat patches for terrestrial vertebrate species to predict the likely number of species that will be sustained on the landscape. The spatially explicit economic model incorporates site characteristics and location to predict economic returns for a variety of potential land uses. We apply the model to search for efficient land-use patterns that maximize biodiversity conservation objectives for given levels of economic returns, and vice versa. We apply the model to the Willamette Basin, Oregon, USA. By thinking carefully about the arrangement of activities, we find land-use

Conjoint analysis is a statistical technique used to elicit partworth utilities for product attributes from consumers to aid in the evaluation of market potential for new products. The objective of the share-of-choice problem (a common approach to new product design) is to find the design that maximizes the number of respondents for whom the new product’s utility exceeds a specific hurdle (reservation utility). We present an exact branch-and-bound algorithm to solve the share-of-choice problem. Our empirical results, based on several large commercial data sets and simulated data from a controlled experiment, suggest that the approach is useful for finding provably optimal solutions to realistically sized problems, including cases where partworths contain estimation error.

The introduction of the evolutionary solver in Frontline Systems' Premium Solver for Education allows students to use any functions in Excel for modeling optimization problems. As a result, instructors teaching optimization now face a dilemma of how much emphasis to place on “traditional” integer programming versus the unrestricted but heuristic approach of the evolutionary solver. Our goal in this work is to shed some light on the tradeoffs in these two modeling approaches. We discuss some experimental results comparing the two approaches for a number of well-known problem types. We also report some observations of student performance with these two different approaches.

Decision makers involved in land acquisition and protection often have mul- tiple conservation objectives and are uncertain about the occurrence of species or other features in candidate sites. Models informing decisions on selection of sites for reserves need to provide information about cost-efficient trade-offs between objectives and account for incidence uncertainty. We describe a site selection model with two important conser- vation objectives: maximize expected number of species represented, and maximize the likelihood that a subset of endangered species is represented. The model uses probabilistic species occurrence data in a linear-integer formulation solvable with commercial software. The model is illustrated using probabilistic occurrence data for 403 terrestrial vertebrates in 147 candidate sites in western Oregon, USA. The trade-offs between objectives are explicitly measured by incrementally varying the threshold probability for endangered species representation and recording the change in expected number of species represented. For instance, in the example presented here, we found that under most budget constraints, the probability of representing three endangered species can be increased from 0.00 (i.e., no guaranteed protection) to 0.90 while reducing expected species representation ;2%. However, further increasing the probability of endangered species representation from 0.90 to 0.99 results in a much larger reduction in species representation of ;14%. Although the numerical results from our analysis are specific to the species and area studied, the meth- odology is general and applicable elsewhere.

We analyze the problem of maximizing the expected number of species in a nature reserve network, subject to a constraint on the number of sites in the network, given probabilistic information about species occurrences. The problem is a nonlinear binary integer program that is NP-hard. We develop a linear integer programming approximation that may be solved with standard integer programming software. We compare the approximation with two other approaches, an expected greedy approach and a probability hurdle approach, using probabilistic data on occurrences of terrestrial vertebrates in the state of Oregon. Results of the approximation and an exact algorithm are compared by using samples from the North American Breeding Bird Survey.

Concerns that the loss of habitat have greatly increased species extinction rates has led to calls for establishing biological re- serves to preserve key habitat. In this paper, we study reserve site selection for terrestrial verte- brates in Oregon using data on species ranges and land values. We ® nd cost-effective strategies that represent a maximum number of species for a given conservation budget. By varying the bud- get, we ® nd the cost of obtaining various levels of representation. In general, effective conservation decision-making requires integrated analysis of both biological and economic data. (JEL Q20)

CPMS, the Practice Section of INFORMS, strives to support OR/MS practitioners by publicizing OR/MS success stories and by connecting professionals with similar interests. We are therefore pleased to present the results from the 2009 competition for the Daniel H. Wagner Prize for Excellence in Operations Research Practice, established in memory of the late Dr. Daniel H. Wagner. Dan Wagner earned his PhD in mathematics from Brown University in 1951. His dissertation, “On free products of groups,” was published in Transactions of the American Mathematical Society in 1957. Dr. Wagner began his career in the US Navy’s Operations Evaluation Group (OEG) at the Pentagon, where he worked on operations research for naval warfare. He worked there until 1956, with a one-year leave of absence for postdoctoral research on free algebras at MIT. Dan then joined Burroughs Research Center, where he directed a group of mathematicians performing analysis for the development of digital computers. In 1957, Dan’s entrepreneurial spirit took over, and together with Dr. John D. Kettelle, he formed the partnership of Kettelle and Wagner, which was dissolved in 1963. That same year, he formed a new company, Daniel H. Wagner Associates, Inc. This company did leading-edge work in the mathematics of naval tactics, especially antisubmarine warfare, detection theory, and search planning. During his years as president and principal owner of Wagner Associates, Dan brought many highquality mathematicians into the operations research community. This led to significant advances in the firm’s fields of endeavor and delivery of significant applications to the Navy, Coast Guard, and other clients; many of these applications are still in service today. After retirement from his eponymous company, Dan continued his commitment to the field of operations research, serving in various teaching and research positions with the US Naval Postgraduate School and the US Naval Academy. He was an active member of ORSA, and then INFORMS, for more than 40 years. The idea for this prize began at Dan’s memorial service in April 1997, where many of his former colleagues gathered. Following the agreements made on that day and the subsequent pledges, the firms Metron, Inc., Daniel H. Wagner Associates, Inc., and Applied Mathematics, Inc., generously donated a total of $51,000 as an endowment to ensure the availability of a cash award in perpetuity. Each of these companies is an outgrowth in large part of Dan’s early efforts. Metron, Inc. (President and COO Tom Corwin, http://www.metsci.com) is a scientific consulting company dedicated to solving challenging problems in national defense through the development and application of advanced mathematical methods. Problem solutions are realized using computer software with graphical interfaces that allow a user to understand and act on the results without having to comprehend the intricacies of the models themselves.

In 1993, Procter & Gamble (P&G) began an effort entitled strengthening global effectiveness (SGE) to streamline work processes, drive out nonvalue-added costs, and eliminate duplication. A principal component of SGE was the North American product supply study, designed to reexamine and reengineer P&G's product-sourcing and distribution system for its North American operations. The methodology developed to solve this problem drew on OR/MS and information technology, merging integer programming, network optimization models, and a geographical information system (GIS). As a result of this study, P&G is reducing the number of North American plants by almost 20 percent, saving over $200 million in pretax costs per year and renewing its focus on OR/MS approaches.

We investigate the effects of setup time and cost reduction through learning on optimal schedules in the capacitated lot sizing problem. Dynamic demand and time varying capacity is assumed. The scheduling effects are discussed, along with exact and heuristic approaches to solving these planning problems.

Government cost analysts must often construct models using production data that are limited by a contract between the producer and the government. The producer usually does not share cost data with the government unless the contract requires that data are reported. Also, the data that are reported are often not in the proper form for constructing mathematical models; that is, cost data are often provided by production unit or lot, while economic and accounting data are usually reported by time period. This paper provides a mathematical link between unit or lot data and time series data; that is, between the units domain and the time domain. The analysis is relevant for made-to-order production, the case where a relatively small number of specialized items are produced to contractual order, as in defense and other government contract situations.

The capacity constrained lot sizing problem with learning is modeled as a nonlinear mixed integer program. Three solution techniques for solving the model are investigated. A nonlinear programming package together with the branch and bound technique is used to obtain a solution to the exact problem. The issue of nonconvexity is discussed. In the piecewise linearization of the learning curve, the problem is represented by a mixed integer programming model. Finally, a heuristic that gives near optimal solutions in minimal computer time is developed. Process learning results in a reduction in the number of setups and an increase in inventory level.

The importance of sensitivity analysis information in linear programming has been stressed in the management science literature for some time. Indeed, Gal [3] has devoted an entire text to just this issue. Linear programs with common inputs (cost coefficients or right-hand-side values) present a problem in that classical sensitivity analysis does not allow for the simultaneous changes required to determine the sensitivity of these models to common inputs. We first survey the approaches previously developed for simultaneous-change sensitivity analysis and cast them in the framework of the special common input case. These general techniques are compared to a simple aggregate variable technique that has not received attention in the literature.

Some texts and applied research papers continue to advocate the use of “M,” an “extremely large number,” in modeling a fixed charge in binary integer programs. This choice of M can be very detrimental to solving even reasonably sized problems. Previous research provides straightforward techniques which should be implemented by any person intelligent enough to develop an MIP model.

High-value-added manufacturing companies today confront a competitive trend toward greater product customization in the face of reduced response times. This scenario is encountered most often in industries like machine tools, heavy construction equipment, heavy manufacturing in general and computer software and hardware. The product is highly customized, yet competition requires manufacturers to deliver it with lead times significantly shorter than the manufacturing lead time. Generally, the scheduling practice here is to release the manufacturing order before the customer order is released and subsequently match incoming customer orders to units in progress. This is referred to as the “build-to-forecast” (BTF) approach. This study investigated the coping mechanisms used by manufacturing firms to alleviate this dilemma. The tactics vary with the firm's business strategy, its operating environment, and its capabilities. We report on three case studies from firms building heavy machinery. The firms are similar in terms of the range of final product values, build times, customer delivery times and the very large number of components. Also, their operations require the use of a variety of flexible and dedicated resources. Flexibility in manufacturing processes, modular bills of materials, subcontracting and expediting are some of the approaches that these firms use to help resolve the double bind of short lead times and high levels of customization. We review some of the operational problems peculiar to the build-to-forecast environment and suggest alternative approaches for dealing with them. The coping mechanisms are grouped according to the manner by which they help relieve the BTF problem's severity. One set of mechanisms makes the problem less complex by simplifying products or the production process. Another set reduces the risks due to uncertainty in demand or supply. The third set provides engineering and manufacturing slack. While some or all of the mechanisms are used by the manufacturing firms studied, the predominance of particular mechanisms in each firm is explained by a contingency model developed in this paper. The case studies provide useful insights into the nature of the problem and how the firm's organizational environment often dictates the choice of mechanisms used to alleviate it. For example, these firms minimized their scheduling dilemmas with modular product designs, flexible processes, informal organization structures, or formal control mechanisms for limiting customization. We conclude by framing a number of research questions whose solutions would help such firms better manage their operations.

We develop a branch-and-price algorithm for constructing an optimal product line using partworth estimates from choice-based conjoint analysis. The algorithm determines the specific attribute levels for each multiattribute product in a set of products to maximize the resulting product line's share of choice, i.e., the number of respondents for whom at least one new product's utility exceeds the respondent's reservation utility. Computational results using large commercial and simulated data sets demonstrate that the algorithm can identify provably optimal, robust solutions to realistically sized problems.

Efforts at species conservation in the United States have tended to be opportunistic and uncoordinated. Recently, however, ecologists and economists have begun to develop more systematic approaches. Here, the problem of efficiently allocating scarce conservation resources in the selection of sites for biological reserves is addressed. With the use of county-level data on land prices and the incidence of endangered species, it is shown that accounting for heterogeneity in land prices results in a substantial increase in efficiency in terms of either the cost of achieving a fixed coverage of species or the coverage attained from a fixed budget.

This is my last issue as editor in chief of Interfaces. I have to say, being editor in chief has been one of the most rewarding experiences of my career. This issue also marks the 40th year of Interfaces. I believe it remains the undisputed premiere journal of OR practice. At the time of this writing, my successor has not yet been named. Before giving a little detail about the contents and theme for this special issue, I want to thank the many people who have helped me along the way in my six years as editor in chief. Thanks to all of the members of the editorial board. Their dedication to a highquality and efficient review process has made my job much easier. Thanks, too, to all of the many reviewers who, along with the board, have kept our standards high. At 11 percent, our acceptance rate remains low. I also offer a heartfelt thank you to the editorial staff: Kelly Kophazi, Alice Barrett Mack, Candita Gerzevitz, Stephanie Myers, and Pat Shaffer, Director of Publications. It truly has been a pleasure working with you. A special thanks to Kelly. She has been with me since day one. Together, we transitioned from paper to electronic submissions and then to Manuscript Central. On more than one occasion, it was Kelly who kept the train rolling. Thanks to all of you who read Interfaces and have taken the time to let me know what you really liked and what could be improved. I hope, like my predecessors, that I have left the journal a little better. I decided to mark this 40th anniversary of Interfaces with an issue consisting of papers by authors whom I consider to really be on the interface between theory and practice. I approached Sridhar Tayur (Carnegie Mellon and SmartOps) about telling us what he has learned from being simultaneously a very successful academic and entrepreneur. After struggling a bit to come up with something new, we decided to talk about monetizing the value of OR. As you will see, it is a different style of paper. David Miller of the University of Alabama has been director of the Alabama Productivity Center for many years. The center’s mission is to improve Alabama companies’ quality, productivity, and competitiveness through the use of the university’s research and educational resources. I invited David to tell his story, so that others may learn what has worked and what has not worked in trying to do practice in an academic setting. Mike Gorman of the University of Dayton, winner of the 2010 INFORMS Prize for the Teaching of OR/MS Practice, has written about practice in the classroom. Many have written about this. Very few have implemented it more enthusiastically than Mike. I believe what he has done should serve as a model for those of us in academia who care about practice and about creating successful OR practitioners. Gene Woolsey, Professor Emeritus of the Colorado School of Mines, founding editor of this journal and author of numerous editions of his Fifth Column, summarizes the cumulative impact his program has had at the School of Mines in a Fifth Column for this special issue. I have spoken to Gene several times this year. Although his health is not what it used to be

In his President’s Column in the April 2009 issue or OR/MS Today, INFORMS President Don Kleinmuntz discusses our lack of success as a society in reaching out to practitioners (Kleinmuntz 2009). He mentions that in 2006, the US Department of Labor Statistics estimated that 58,000 individuals were working in operations research (and perhaps another 3 million in closely related fields). However, INFORMS has only about 2,500 practitioner members. I share Don’s concern and believe that we (INFORMS) should aspire to achieve a higher market share of operations researchers in industry, not-for-profit organizations, and government. We need to consider ways to increase our practitioner membership. To this end, INFORMS reaches out to practitioners through its Practice Meeting, the Practice Section, the Roundtable, and the publication of Interfaces and OR/MS Today. In his column, Don questions whether Interfaces is meeting its stated mission: “Interfaces seeks to improve communication between managers and professionals in OR/MS and to inform the academic community about practice.” Don and I have discussed this, and I believe it is the first part of this mission that he questions. I believe that we are improving communication between managers and professionals of OR/MS if both are reading Interfaces. For example, Glenn Wegryn, who manages an OR group at Procter & Gamble, might read an article written by Thomas Olavson of Hewlett-Packard and Chris Fry of Strategic Management Solutions (Olavson and Fry 2008), and take what he learns from the article to his group. Likewise, we occasionally include articles on how to manage OR groups so that an OR manager can communicate to other professionals what he or she learns. Nigam (2008) is an example. Thus, one can argue that Interfaces is indeed meeting both parts of its mission. The bread and butter of Interfaces has been and will continue to be examples of successful applications of operations research. Each year, we publish the finalists of the Edelman and Wagner competitions. We publish contributed columns, such as the Art and Science of Practice, the Ombudsman, and the Fifth Column, as well as Practice Abstracts and Book Reviews. We also occasionally include articles on controversial subjects (see Armstrong et al. 2008) and on lessons learned in the field (see Brown and Rosenthal 2008). Nonetheless, Don’s comments caused me to seriously ponder what is missing and how we might broaden the mix of the types of papers in Interfaces. In the past, Interfaces has published tutorials. The Lagrangian relaxation tutorial by Fisher (1985) is an excellent example of a very useful tutorial and is one of the most cited papers to have appeared in Interfaces. I have used it in the classroom for many years. We seem also to have gotten away from publishing surveys. If you have an idea for a tutorial or survey paper, send me an e-mail with a proposal. With this issue, Ron Fricker of the Naval Postgraduate School joins the board as contributing editor. He accepted my invitation to continue the rankings of university contributions to the OR practice literature that Mike Rothkopf started. The first ranking under Ron will appear in the November–December 2009 issue. We have decided to expand this a bit and, to Don Kleinmuntz’s point, also acknowledge

Iwould like to bring to your attention several important changes that have taken place over the last few months. First, you may have noticed that we have changed the tagline for Interfaces from “An International Journal of the Institute for Operations Research and the Management Sciences,” to “The INFORMS Journal on the Practice of Operations Research.” I feel this is much more descriptive of the mission of Interfaces and the role it plays in the profession. My thanks go to Bruce Golden of the University of Maryland for suggesting the change. Second, my colleague Uday Rao of the University of Cincinnati has served as deputy editor since 2005. Uday has decided to step down because of an increase in his other responsibilities. Uday, thank you for your service to this journal. Mike Gorman of the University of Dayton has joined the board as new deputy editor. Welcome aboard, Mike. Finally, Candi Gerzevitz has been the production editor throughout my tenure as editor in chief. Candi, I appreciate the superb job you have done in tending to all the details to make sure that the journal gets to and through production and into readers’ hands. Working with you over the last four years has been an absolute pleasure. Best of luck to you with your new assignments with INFORMS. Stephanie Trickey is the new production editor for Interfaces. Stephanie has hit the ground running and we welcome her to the team.

In the following pages, you will find a provocative piece by Armstrong, Green, and Soon, commentaries on this work by Cochran, Goodwin, and Murphy, and a follow-up reply by Armstrong, Green, and Soon. A controversial decision to list or not list the polar bear as an endangered species became even more controversial when the decision took much longer than expected. On May 14, 2008, three years after the filing of the original lawsuit to force consideration of polar bears as endangered, US Secretary of the Interior Dirk Kempthorne announced the decision to list the polar bear as threatened, that is, on track to be listed as endangered. Part of the reason given for the delay in reaching a decision was the overwhelming amount of scientific evidence that needed to be considered. Armstrong, Green, and Soon were involved in that evaluation process. On January 30, 2008, lead author Scott Armstrong testified before the US Senate Committee on Environment & Public Works regarding the authors’ forecasting audit of a set of listing-decision studies under consideration. Shortly thereafter, Scott, who is a contributing editor of Interfaces, approached me about the possibility of Interfaces publishing their audit work. (Scott and his coauthors had sent it to another journal, but were having trouble getting a decision.) They withdrew the paper from consideration by the other journal and submitted it to Interfaces, which accepted it after several efficient rounds of refereeing, Scott encouraged me to solicit commentaries on their work, and Jim Cochran, Paul Goodwin, and Fred Murphy came through in a timely way. Steven Amstrup, Research Wildlife Biologist at the United States Geological Survey’s Alaska Science Center, is an author of one of the studies that Armstrong, Green, and Soon audited. In March, I invited Dr. Amstrup to submit a rebuttal. His fieldwork responsibilities prevented him from responding in time for this issue, but he has accepted my invitation and has indicated he will submit a rebuttal in the near future. We look forward to his contribution. I encourage you to read these pieces with an open mind and ponder the role, indeed the responsibility, we have as analysts to support good decision making in the public sector.

The OR community at large, and the OR practice community in particular, lost two great leaders this year. Rick Rosenthal passed away on January 3, 2008 after a hard-fought battle with cancer. Mike Rothkopf died unexpectedly on February 18, 2008 while swimming at the McCoy Natatorium at Perm State University. In this issue we have two papers to honor these colleagues who were so supportive and involved in OR practice. Rick Rosenthal was a Distinguished Professor at the Naval Postgraduate School in Monterey, California. I knew Rick for over 20 years. He was very much focused on practice and solving real-world prob lems. He was instrumental in getting young faculty involved in the INFORMS Practice Meeting held each spring. Last year I became aware of a talk Rick and Jerry Brown had been giving on practical optimiza tion. After some prodding from me, Rick and Jerry began the process of transforming their talk into an Interfaces paper. Their paper, "Optimization Trade craft: Hard-Won Insights from Real-World Decision Support," appears in this issue. I thank Jerry for seeing the paper through to completion. I believe aca demics and practitioners (and those of us who con sider ourselves in the intersection) will find this paper very informative. As someone who teaches optimiza tion, I certainly plan to use it in my classes. Mike Rothkopf, past president of INFORMS and former editor in chief of this journal, had long been very active in OR practice. Mike had just joined Penn State in the fall of 2007 after many years at Rut gers. I also knew Mike for a long time. When I became the editor in chief of Interfaces, Mike went out of his way to offer me advice based on his experi ence. He also always had provocative and encourag ing words for academics focused on practice. Mike was probably most famous for his work on auctions, and so it is fitting that his colleagues Ron Harstad and Aleksandar Sasa Pekec have written a paper on auctions in Mike's honor. Their paper, "Relevance to Practice and Auction Theory: A Memorial Essay to Michael Rothkopf," appears in this issue. It illustrates just how significant Mike's contributions to auctions were and how he emphasized the need to focus on practice. We mourn the loss of these two great friends and colleagues and remain grateful for their contributions and the impact they have had on the profession.

Iam pleased to announce that we have a number of new editorial board members joining our team with this issue. Alexandra Newman of the Colorado School of Mines will serve as an editor-at-large and will handle papers in optimization. Rich Metters of Emory University will be an associate editor of operations management, with a focus on service operations. You will also notice in this issue that Mohan Sodhi is now the guest editor for the Edelman issue. He will serve in that role for three years. Thanks to all of these folks for agreeing to serve Interfaces and to all of the continuing board members for their dedicated service.

I have made several additions to the editorial board and am planning a new special issue.

Jeffrey D. Camm begins his term as editor-in-chief of Interfaces.

Economists have used frontier analysis for some time now to measure the efficiency of the firm. Recently, particularly since the development of data envelopment analysis, management scientists have applied efficient frontier analysis to a variety of problems. We used linear programming to estimate a frontier function that describes where the age records for a particular running race should be, given the current records. The frontier function is used to handicap running races based on age and sex. The frontier method is an improvement over current methods in that it avoids the problem of soft records for some ages.

Learning curve theory has been integrated into mathematical models which previously did not take learning into account. Researchers have in general used one of two approximations of total cost based on the integral of the unit learning curve when developing larger models. An error analysis of the two approximations is presented.

The advent of the wide variety of new, highly integrated, advanced manufacturing technologies available for acquisition by a firm's managers has brought to light an accompanying set of unexpected issues. These issues include expectations for the benefits and costs of these technologies, determining the appropriate order of implementation and finding a way to justify acquisition when many of the benefits are a function of the technology's learning and synergistic effects on other operations and technologies. We present here a model that captures the interaction effects of these highly integrated technologies and discuss the data requirements for application of the construct. We then illustrate the model's workings with a number of multitechnology examples and show the danger of ignoring the synergistic and learning effects of these technologies when considering their acquisition.

This note describes differences in the feasible range of values that the learning curve parameter may take when a unit learning approach is used as opposed to a cumulative-average learning curve. Clarification of this point is important because learning curve theory now is used in a variety of areas.