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Billerud, a Swedish company with four integrated pulp and paper mills, serves specific packaging-market segments. In 2000, the process-engineering department at Billerud's mill in Skärblacka sought to improve the mills' bleaching process. It contacted Linköping University, which collaborated with Eurocon Automation AB to develop a decision-support system, OptCab. Eurocon Automation AB now offers OptCab as a general tool in the market. Its core is an online optimization system that dynamically updates a process description and optimizes the bleaching control process. The system, which has been fully operational since 2004, has provided numerous benefits to Billerud. Chemical use has decreased by approximately 10 percent, saving approximately two million euros since its installation; the environmental impact has also been reduced; and the brightness quality of paper that the mill produces is more uniform and stable. Moreover, OptCab requires less operator time, freeing the operators for development and analysis work. [ABSTRACT FROM AUTHOR]

It is often claimed that managers do not read serious research papers in journals. If true, this neglect would seem to pose a problem because journals are the dominant source of knowledge in management science. By examining results from the forecasting principles project, which was designed to summarize all useful knowledge in forecasting, we found that journals have provided 89 percent of the useful knowledge. However, journal papers relevant to practice are difficult to find because fewer than three percent of papers on forecasting contain useful findings. That turns out to be about one useful paper per month over the last half century. Once found, papers are difficult to interpret. Managers need low-cost, easily accessible sources that summarize advice (principles) from research; journals do not meet this need. To increase the rate of progress in developing and communicating principles, researchers, journal editors, textbook writers, software developers, Web-site designers, and practitioners should make some changes. We offer some examples: Researchers should directly study forecasting principles. Journal editors should actively solicit papers; invited submissions were about 20 times better than standard submissions at producing useful findings that were often cited, and they do so at lower cost. Textbook writers should focus on principles so that readers can apply knowledge. Web-site and software developers should provide practitioners with low-cost ways to use principles. Practitioners should apply the principles that are currently available. [ABSTRACT FROM AUTHOR]

Distribution networks of many logistics service providers have evolved from single-depot to complex, dynamic multidepot networks. In a single-depot network, the deliveries from each depot are planned for that depot only, and drivers return to the starting depot to pick up each new order. In a multidepot network, the deliveries from multiple depots can be planned simultaneously; therefore, a logistics service provider can efficiently combine its resources, thus reducing its labor and transport costs. However, an increasing emphasis on reliability, customization, and flexibility is affecting the logistics structures. This paper describes the shift from single-depot planning to multidepot planning for Nabuurs B.V., a large Benelux logistics service provider that implemented a centralized, automated multidepot planning process throughout its organization. We developed a simulation model to evaluate system performance and to address performance challenges. In this paper, we discuss the results of extensive simulation tests and the specific recommendations that Nabuurs B.V. management implemented. [ABSTRACT FROM AUTHOR]

Kolon Sport (K/S), a leading outdoor fashion brand in South Korea, must deal with a large variety of items during each selling season. In doing so, the company has encountered a challenging operational problem-the assort-packing and distribution problem. The problem involves making decisions on the optimal method to use in packing a set of different items in a box and allocating the boxes to stores to meet the stores' demands. In this paper, we introduce an analytics project initiated to improve the assort-packing and distribution process, and we describe the formulation and solution approach we developed to solve this industrial problem in a timely manner. We validated the proposed approach by computational and onsite pilot testing, which demonstrated that the decisions made using this approach are superior to those made with the manual method K/S used previously. Inventory is distributed to all stores in a more balanced way by considering the demands of the stores. K/S, which implemented the proposed approach into its internal system in July 2015, estimates that the new system improves sales by approximately eight percent. [ABSTRACT FROM AUTHOR]

During a single planning period, Kimberly-Clark Latin America manufactures dozens of stock-keeping units (SKUs) in varying quantities using a few machines. The same SKU can be manufactured on multiple machines, some of which are more efficient than others. In addition, the setup time for an SKU is sequence dependent, and its demand is stochastic between planning periods. The stochastic demand necessitates changing production plans each planning period; given the large number of SKUs and small number of machines, this leads to inefficiencies. This paper describes the formulation and corresponding solution approach of an integrated inventory, production-planning, and detailed scheduling model to address the inefficiencies in lot sizing, production scheduling, and inventory management. The paper's key contribution is the solution approach, which solves the resultant industry-size NP-hard problem in minutes. The solution quality and its implementation have been tested extensively, and the model has been successfully deployed in five countries. A reduction in finished product inventories of up to 45 percent, an increase in yield and uptime of 2 percent, and improvements in service levels of 2.4 percent are directly attributable to the model and the solution approach highlighted in the paper. [ABSTRACT FROM AUTHOR]

The operations management major at the University of Dayton offers a unique capstone experience that features live consulting projects with actual client problems. As a result, students gain valuable experience applying technical skills in a live environment, and clients gain real operations improvements. In the past eight years we have graduated 163 students who have conducted 56 projects for 22 clients. This paper describes how the course is structured, observations of faculty and clients on best practices and risks associated with such an offering, and as evidence of success, the quantitative and qualitative impact the student-led projects have had on clients. [ABSTRACT FROM AUTHOR]

Warranty inventory management is a challenge that many companies must confront. Customers return allegedly defective units to a company for replacement or credit. The company can then economically recover the unit through either a testing or remanufacturing process; it can use recovered units to fulfill future warranty requests. The company also has the option of purchasing a new product from the production line. In high-volume situations, warranty inventory management involves many complexities such as stochastic demand rates, probabilistic requests for credit instead of replacement, probabilistic repairs, multiple sources of supply, and tight customer-service constraints. Companies may also have to consider the complexities that a batch remanufacturing process causes. In this paper, we formulate several related models of such warranty inventory systems. In these models, we study a periodic, single-location, inventory system that is dedicated to warranty returns. We find near-optimal policies for each system using well-developed heuristics. The models include the following complexities: random warranty claims, random requests for replacement or credit, three sources of supply (testing, remanufacturing, and new product), random flows of returned products into testing and remanufacturing, random yields from testing and remanufacturing, different lead times for each resupply process, remanufacturing lead time variability, and random batching of remanufacturing. The results of the models provide near-optimal inventory-control policies in this complex environment and demonstrate the payoffs that result from reducing production lead times and batching in remanufacturing. Hitachi GST has gained a great deal from this modeling process. In addition to the direct benefit from the model's calculations, additional sensitivity analyses have shed light on the quantitative importance of various factors, including demand volatility, the percentage of credit requests, the percentage of units successfully remanufactured, and batching effects in remanufacturing. [ABSTRACT FROM AUTHOR]

The U.S. Navy operates an impressive fleet of nuclear-powered submarines and aircraft carriers and has safely operated its nuclear fleet for more than 60 years, while steaming over 154 million miles. Rigorous training has been key to maintaining such an impressive record. The U.S. Naval Nuclear Propulsion Training Program develops, certifies, and delivers the nuclear-operator qualification training for enlisted and officer personnel operating its nuclear fleet. This training finishes at one of four nuclear-power training units (NPTUs), operates under a complex set of hard and soft constraints, varies depending on the type of student, and requires significant personnel and equipment resources. We developed and implemented a mixed-integer linear program (MILP) that prescribes how many students of each type to allocate to each NPTU at the start of each class (a group of students who train together) and how allocated students complete NPTU training. The use of MILPhas improved student allocation by an estimated eight percent and led to significantly improved use of bothNPTUpersonnel and equipment resources. In this paper, we describe this unique optimization application, the MILP formulation, its path to adoption, its user interface, and impacts from its development and use over the past three years. [ABSTRACT FROM AUTHOR]

In this paper, we discuss our development of a life-of-mine production plan for Barrick Gold Corporation's Lumwana operation, a large copper mining complex based on the Chimiwungo and Malundwe reserves. In our production plan, we maximize recovered copper metal based on a mixed-integer program (MIP) formulation with reserve aggregations that approximate those used in operational mine planning. We discuss the application of a MIP to medium-term planning based on a 60-month production schedule. Constraints on shovel placement, uranium levels in mill feed, stockpiling and mining, and processing capacity ensure that the resulting production schedules and resource allocation are operationally feasible. At Lumwana, our MIP solution strategies optimize the scheduling problem at two levels of time and production-volume granularity. A coarse solution based on annual production from aggregated reserve blocks sets the overall production strategy. This strategy is then imposed on a schedule of monthly production for the scheduling volumes used in actual production planning. This problem was not solvable as a single multiperiod monolith. Instead, we solved a sequence of overlapping multiperiod problems in which each subproblem advances the schedule horizon a given number of periods while fixing the solution to the initial periods of the previous subproblem. We solve multiple options relating to production capacity with a life-of-business optimization system (LOBOS) that we developed. [ABSTRACT FROM AUTHOR]

In this paper, we describe the model, theory developed, and deployment of PROTECT, a game-theoretic system that the United States Coast Guard (USCG) uses to schedule patrols in the Port of Boston. The USCG evaluated PROTECT's deployment in the Port of Boston as a success and is currently evaluating the system in the Port of New York, with the potential for nationwide deployment. PROTECT is premised on an attacker-defender Stackelberg game model; however, its development and implementation required both theoretical contributions and detailed evaluations. We describe the work required in the deployment, which we group into five key innovations. First, we propose a compact representation of the defender's strategy space by exploiting equivalence and dominance, to make PROTECT efficient enough to solve real-world sized problems. Second, this system does not assume that adversaries are perfectly rational, a typical assumption in previous game-theoretic models for security. Instead, PROTECT relies on a quantal response (QR) model of the adversary's behavior. We believe this is the first real-world deployment of a QR model. Third, we develop specialized solution algorithms that can solve this problem for real-world instances and give theoretical guarantees. Fourth, our experimental results illustrate that PROTECT's QR model handles real-world uncertainties more robustly than a perfect-rationality model. Finally, we present (1) a comparison of human-generated and PROTECT security schedules, and (2) results of an evaluation of PROTECT from an analysis by human mock attackers. [ABSTRACT FROM AUTHOR]

In this paper, we present a system that Compañía Sud Americana de Vapores (CSAV), one of the world's largest shipping companies, developed to support its decisions for repositioning and stocking empty containers. CSAV's main business is shipping cargo in containers to clients worldwide. It uses a fleet of about 700,000 TEU containers of different types, which are carried by both CSAV-owned and third-party ships. Managing the container fleet is complex; CSAV must make thousands of decisions each day. In particular, imbalances exist among the regions. For example, China often has a deficit of empty containers and is a net importer; Saudi Arabia often has a surplus and is a net exporter. CSAV and researchers from the University of Chile developed the Empty Container Logistics Optimization System (ECO) to manage this imbalance. ECO's multicommodity, multiperiod model manages the repositioning problem, whereas an inventory model determines the safety stock required at each location. CSAV uses safety stock to ensure high service levels despite uncertainties, particularly in the demand for containers. A hybrid forecasting system supports both the inventory and the multicommodity network flow model. Major improvements in data gathering, real-time communications, and automation of data handling were needed as input to the models. A collaborative Web-based optimization framework allows agents from different zones to interact in decision making. The use of ECO led to direct savings of $81 million for CSAV, a reduction in inventory stock of 50 percent, and an increase in container turnover of 60 percent. Moreover, the system helped CSAV to become more efficient and to overcome the 2008 economic crisis. [ABSTRACT FROM AUTHOR]

Academic outreach and interactions with industry can take on many faces and delivery modes. Some of these efforts focus mainly on student learning, others on supporting faculty research interests, whereas others are primarily university service in nature. This paper reports the experiences of a 24-year initiative that has been successful in touching all three of these bases. We report on the model we have followed, on what has worked for us, and on what has not; we also discuss the lessons we learned that may benefit other universities with initiatives designed to provide a win-win outreach outcome. [ABSTRACT FROM AUTHOR]

Every sports league needs a game schedule; such a schedule is important because it influences all parties involved and even the outcome of the sports competition. Interest in Belgian soccer has increased during recent years, as has interest in sports leagues in other countries. This paper describes our experiences in scheduling the highest division in the Belgian soccer league. We describe how we automated and improved the development of the 2006-2007 season schedule, and explain how we achieved additional improvement by dividing the scheduling problem into two problems. The resulting calendar has been accepted for the 2007-2008 season. We also compare the quality of the schedules generated using different scheduling methods. [ABSTRACT FROM AUTHOR]

As air traffic in the United States has grown over the last several years, traffic demand has begun to outstrip capacity. As of 2005, the Federal Aviation Administration (FAA) had no effective approach for strategically managing a weather event that has been very disruptive to the national aviation system--large-scale thunderstorms that block the major flight routes in the northeastern United States. The operations research team that supports the FAA's efforts to provide innovations in air traffic management, led by researchers at Metron Aviation, Inc. and the Volpe Transportation Center, recognized the consequence of this operational deficiency and set out to resolve it. In this paper, we show how this team (1) developed and applied system-simulation models to quantify the extent of the traffic flow management problem and convey its magnitude to the FAA and to the aviation industry; (2) designed the Airspace Flow Program (AFP), a new approach to managing air traffic that could correct the problem within the limitations of a short development cycle and a change-resistant culture; (3) designed and developed an interactive simulation system that could be and was used to refine and perfect this concept prior to deployment by developing policies on the use of a decision support system; (4) engaged FAA and airline traffic management experts in a series of interactive exercises using the simulation system to develop the final software design, operational procedures, and decision rules for deployment and use; and (5) provided a clear and convincing postdeployment benefits assessment for the new traffic management approach. The deployment of this new capability was an enormous success that both the FAA and the airline community heralded widely. The postdeployment impact assessment showed benefits to the aircraft operators and the flying public of almost $190 million in 2006 and 2007, the first two years of use, compared to less than $5 million in design and development costs. Broader usage of AFPs and new applications for them show a projected 10-year benefit of approximately $2.8 billion. [ABSTRACT FROM AUTHOR]

In this paper, we describe how Delphi Corporation used simulation in the concept-development phase of a new multimillion-dollar fuel injector production line. Delphi wanted to assess the financial viability of production targets and identify the critical features of the line on which it would focus its design-improvement efforts. [ABSTRACT FROM AUTHOR]

The article discusses the use of an optimization approach to improve scheduling within robotic cells for FSI International Inc., a company that designs and manufactures robotic cells for wafer-fabrication companies. A robotic cell is a manufacturing system used in a variety of industries, including wafer fabrication. A wafer-fabrication cell contains several robot-served processing stations and produces identical wafers repetitively. Each wafer is processed through processing stations or stages as in a stage flow shop, and there are no buffers at or between the processing stations. Since a single type of wafer is produced, the optimal schedule is simply the sequence of robot moves that maximizes the throughput or, equivalently, minimizes the per-unit cycle time or the average time to produce a part in steady state. Since wafers are very valuable, even a small increase in throughput may lead to a substantial increase in profit. Consequently, throughput is a critical issue for the wafer-fabrication companies that are FSI's clients.

Investigating the causes of aircraft failures and preventing their reoccurrence are crucial to achieving and maintaining a high flight safety level; technical failure-analysis teams usually perform these functions. We developed and applied a dual-phased process to improve the investigative procedures that these teams use. In the first phase we used a Kaizen method to reconstruct the investigation process. In the second phase we created a simulation model of the resulting stochastic processing network to evaluate alternative configurations. The results indicated a significant improvement in throughput time and investigation quality. In addition, this unique improvement process could be adapted for use by the many organizations that concurrently run several types of jobs (or projects) in a stochastic and dynamic environment. [ABSTRACT FROM AUTHOR]

The US Environmental Protection Agency (EPA) is the lead federal agency for the security of drinking water in the United States. The agency is responsible for providing information and technical assistance to the more than 50,000 water utilities across the country. The distributed physical layout of drinking-water utilities makes them inherently vulnerable to contamination incidents caused by terrorists. To counter this threat, the EPA is using operations research to design, test, and deploy contamination warning systems (CWSs) that rapidly detect the presence of contaminants in drinking water. We developed a software tool to optimize the design process, published a decision-making process to assist utilities in applying the tool, pilot-tested the tool on nine large water utilities, and provided training and technical assistance to a larger group of utilities. We formed a collaborative team of industry, academia, and government to critique our approach and share CWS deployment experiences. Our work has demonstrated that a CWS is a cost-effective, timely, and capable method of detecting a broad range of contaminants. Widespread application of these new systems will significantly reduce the risks associated with catastrophic contamination incidents: the median estimated fatalities reduction for the nine utilities already studied is 48 percent; the corresponding economic-impact reduction is over $19 billion. Because of this operations research program, online monitoring programs, such as a CWS, are now the accepted technology for reducing contamination risks in drinking water. [ABSTRACT FROM AUTHOR]

Xerox has invented, tested, and implemented a novel class of operations-research-based productivity-improvement offerings, trademarked LDP Lean Document Production® solutions, for the $100 billion printing industry in the United States. These solutions, which Xerox has implemented in approximately 100 sites to date, have provided dramatic productivity and cost improvements for both print shops and document-manufacturing facilities, as measured by reductions of 20-40 percent in revenue-per-unit labor cost. They have generated approximately $200 million of incremental profit across the Xerox customer value chain since their initial introduction in 2000. The offerings have extended the use of operations research to small-and medium-sized print shops, while increasing the scope of its application to large document-production facilities. [ABSTRACT FROM AUTHOR]

Accurate forecasts are crucial to successful organizational planning. In 2001, 40 international experts published a set of principles to guide best practices in forecasting. Some of these principles relate to the use of management judgment. Most organizations use judgment at some stage in their forecasting process, but do they do so effectively? Although judgment can lead to significant improvements in forecasting accuracy, it can also be biased and inconsistent. The principles show how forecasters should use judgment and assess its effectiveness. We conducted a survey of 149 forecasters to examine the use of judgment based on these established principles and to investigate whether their forecasting procedures were consistent with the principles. In addition, we conducted four in-depth case studies. Although we found examples of good practice, we also discovered that many organizations would improve forecast accuracy if they followed basic principles such as limiting judgmental adjustments of quantitative forecasts, requiring managers to justify their adjustments in writing, and assessing the results of judgmental interventions. [ABSTRACT FROM AUTHOR]

In September 2003, America West Airlines implemented a new aircraft boarding strategy that reduces the airline's average passenger boarding time by over two minutes, or approximately 20 percent, for full and nearly full flights. The strategy, developed by a team of Arizona State University and America West Airline's personnel, is a hybrid between traditional back-to-front boarding and outside-inside boarding used by other airlines. Field observations, numerical results of analytical models, and simulation studies provided information that resulted in an improved aircraft-boarding strategy termed reverse pyramid. With the new boarding strategy, passengers still have personal seat assignments, but rather than boarding by rows from the back to the front of the airplane, they board in groups minimizing expected passenger interference in the airplane. The analytical, simulation, and implementation results obtained show that the method represents a significant improvement in terms of boarding time over traditional pure back-to-front, outside-inside boarding strategies. [ABSTRACT FROM AUTHOR]

Business schools increasingly pressure faculty members to prepare MBA students to immediately contribute to their employers' bottom lines. Many academics have had little or no business experience themselves, and administrators are encouraging them to acquire it to improve their classroom effectiveness. My guidelines to help faculty get involved with the business community concern handling the initial contact with a company, developing a proposal, managing the project, and following up to ensure successful implementation. I seek to help the faculty member get the r in the word contact to convert it into contract. I focus on operations management and management science, and my intent is to start a process of sharing ideas that encourages others to add to the set. [ABSTRACT FROM AUTHOR]

We developed a simulation approach to reduce the time and cost of selling the Maxager system, a manufacturing decision-support system consisting of both hardware and software. To enable customers to understand the impact Maxager could have on their profitability, we used to perform pilot studies in which we installed our hardware, trained their people, collected data, and performed the analysis. These pilot studies lasted for three to six months and cost hundreds of thousands of dollars. To save time and money, we simulated Maxager data-collection systems and used the Maxager software to analyze the data. This enabled us, with some aggregate information provided by the prospective customers, to illustrate the impact Maxager could have on their systems using simulated data of their products, processes, and operating procedures without having to install our hardware. As a result, (1) we reduced sales cycles from over 12 months long to less than six months long, and (2) we reduced the cost of a sales cycle by approximately $50,000 to $100,000. We achieved these results without a drop in the success rate of the sales process. [ABSTRACT FROM AUTHOR]

A medium-sized consulting firm uses constraint programming to plan its annual meetings of groups of partners to conduct personnel reviews of its consultant-employees. Key constraints include discussing every knowledgeable partner-consultant relationship in at least one meeting; keeping meetings manageable by limiting the number of partners attending and the number of consultants discussed; restricting the number of meetings each partner attends; and requiring the partners who attend each meeting to represent multiple practice areas. Our objective is to minimize the number of situations in which a consultant who is discussed at a meeting has only one knowledgeable partner attending the meeting. Running the model has saved partners from attending meetings unnecessarily and reduced the time required to develop a meeting plan from a few days to a few hours. It has been part of the review-planning process for the past two and a half years. [ABSTRACT FROM AUTHOR]

In a wave of litigation that has escalated into several class-action lawsuits, banks have been charged with sequencing checks unfairly to obtain higher fees for not-sufficient funds (NSF). The point of contention is the banks' use of the high-low check-sequencing procedure, which presents checks for payment in descending dollar amounts. While it is likely that sequencing plays an important role in determining NSF fees, no studies rigorously analyze the theoretical and empirical properties of different sequencing policies and their financial impact on banks and customers. At the request of a litigation participant, we undertook such a study. We interwove several OR/MS tools, including distribution setting, simulation, and integer programming. Our results show that sequencing is only half of the story; the other half concerns the role of overdraft protection. By clarifying the impact of check-sequencing policies, our study should help policy makers, regulators, and courts to arrive at a suitable resolution of the issues surrounding the public-policy debate on check-sequencing. [ABSTRACT FROM AUTHOR]

Many trade events include appointments between buyers and sellers. Each buyer indicates preferences for meetings with various sellers and vice versa. We developed an assignment model and implemented it in the SATE (scheduling appointments at trade events) software. SATE maximizes an objective that weights the preferences of buyers and sellers. Our assignment method schedules more meetings with higher preferences in less computational time than the previous method used. SATE allows organizers of trade events to control appointment scheduling and investigate various scenarios prior to publishing appointment schedules. [ABSTRACT FROM AUTHOR]

In the late 1970s, traffic volumes over the next decade were predicted to double on Canadian National Railway's already congested single track main line. As part of a plant expansion program, a transportation planning research team developed two "what-if" simulation models to evaluate the relative effect of the many factors influencing main line capacity. When used together, they predict train delay under various track and signal designs, operating methods, and traffic scenarios. We then proposed a package of cost-effective improvements for capacity expansion, which included closely spaced inter-mediate signals and strategically located sections of double track. These improvements, together with the application of the simulation models to plant design, have enabled CN to defer capital expenditures of over C$350 million beyond the 1980s. [ABSTRACT FROM AUTHOR]