Showing papers in "Interfaces in 1997"
TL;DR: A spatial decision support system (SDSS) successfully integrates stand-alone PC-based geographic-information-system software with scheduling heuristics and databases to form a user-friendly tool that saves the association travel time and schedule-preparation time and improves the balance of work among nurses.
Abstract: Currently over 10,000 organizations in the United States provide nursing-related services in patients' homes. These organizations face an interesting manpower-deployment decision problem—scheduling which available nurse to see which patient, when, and what travel routes to use. Such issues as adhering to physician-specified requirements on the number of weekly visits make the underlying optimization problem challenging. In a joint project, the University of Alabama's Productivity Center and the Visiting Nurses Association developed a spatial decision support system (SDSS) to address this problem. It successfully integrates stand-alone PC-based geographic-information-system software with scheduling heuristics and databases to form a user-friendly tool that saves the association travel time and schedule-preparation time (over $20,000 a year) and improves the balance of work among nurses.
254 citations
TL;DR: The North American product supply study was designed to reexamine and reengineer P&G's product-sourcing and distribution system for its North American operations, resulting in a reduction in the number of North American plants and a focus on OR/MS approaches.
Abstract: 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.
233 citations
TL;DR: In the early 1990s, National Car Rental faced liquidation, with the loss of 7,500 jobs, unless it could show a profit in the short term.
Abstract: In 1993, National Car Rental faced liquidation. General Motors Corporation (National's parent) took a $744 million charge against earnings related to its ownership of National Car Rental Systems. National faced liquidation, with the loss of 7,500 jobs, unless it could show a profit in the short term. National initiated a comprehensive revenue management program whose core is a suite of analytic models developed to manage capacity, pricing, and reservation. As it improved management of these functions, National dramatically increased its revenue. The initial implementation in July 1993 produced immediate results and returned National Car Rental to profitability. In July 1994, National implemented a state-of-the-art revenue management system, improving revenues by $56 million in the first year. In April 1995, General Motors sold National Car Rental Systems for an estimated $1.2 billion.
214 citations
TL;DR: Cycling between modeling approaches gave benefits that could not have been attained by either hard or soft modeling in isolation and improved the quality of the claim.
Abstract: A contractor to the channel tunnel project instigated litigation to claim for the costs of disruption and delay. We used several interacting models to make the case for the claim more persuasive, coherent, and verifiable. Mixing qualitative modeling large cognitive maps with influence models and with system dynamics simulation modeling improved the quality of the claim. Quality, in this case, being that the modeling process was understandable to the client to the extent that it could argue the claim in court, that every aspect was expected to be transparent to the judge, and that it was robust and defensible management science. Cycling between modeling approaches gave benefits that could not have been attained by either hard or soft modeling in isolation. The claim ultimately was settled satisfactorily out of court with the client acknowledging that the modeling played a significant role.
157 citations
TL;DR: Pontis provides a systematic methodology for allocating funds, evaluating current and future needs of bridges and options to meet those needs, and recommending the optimal policy for each bridge in the context of overall network benefits, budgets, and restrictions.
Abstract: Pontis provides a systematic methodology for allocating funds, evaluating current and future needs of bridges and options to meet those needs, and recommending the optimal policy for each bridge in the context of overall network benefits, budgets, and restrictions. After a trial implementation in California and extensive testing in several states, the system was adopted by AASHTO (Association of American State Highway Officials). Currently, over 40 states are implementing Pontis. At the heart of Pontis is a set of predictive and optimization models which derive their information from judgmental, engineering, and economic models and various databases. The predictive models start with engineering-based subjective inputs and update themselves in a Bayesian context as data is collected. The optimization models consist of interrelated Markov decision models and mathematical programming tools and models.
136 citations
TL;DR: This work uses case studies to highlight how modeling with persistence has improved managerial acceptance and describes how to incorporate persistence as an intrinsic feature of any optimization model.
Abstract: Most optimization-based decision support systems are used repeatedly with only modest changes to input data from scenario to scenario. Unfortunately, optimization (mathematical programming) has a well-deserved reputation for amplifying small input changes into drastically different solutions. A previously optimal solution, or a slight variation of one, may still be nearly optimal in a new scenario and managerially preferable to a dramatically different solution that is mathematically optimal. Mathematical programming models can be stated and solved so that they exhibit varying degrees of persistence with respect to previous values of variables, constraints, or even exogenous considerations. We use case studies to highlight how modeling with persistence has improved managerial acceptance and describe how to incorporate persistence as an intrinsic feature of any optimization model.
86 citations
TL;DR: In this article, the authors developed a selection process for selecting subproblems that reduces the size of the problems solved and improves the quality of the solutions by focusing on solving the weekly and fully dated crew-scheduling problems.
Abstract: Scheduling crews is critical to operating an airline We developed a selection process for selecting subproblems that reduces the size of the problems solved and improves the quality of the solutions By focusing on solving the weekly and fully dated crew-scheduling problems, we developed a natural methodology for solving subproblems that calculates all the possible connections of one day while fixing the connections of all the other days Results with large fleets of many carriers show that this process produces superior solutions to the weekly and fully dated problems even if the daily solution of the crew-scheduling problem is not available Improving the weekly and fully dated problems provides significant benefit and flexibility to the crew-scheduling process Most important, our method allows for the continuous maintenance and support of the solution close to the actual day of operation Traditionally, airlines have fully optimized the daily solution, while optimizing the weekly solution manually T
57 citations
TL;DR: In this paper, the authors show that MS and TQM can be intertwined to attain efficient and cost-effective operations, and they strongly encourage organizations to integrate management science techniques into total quality management (TQM).
Abstract: Management science (MS) and total quality management (TQM) are powerful approaches to improving the operations of organizations. While MS uses quantitative techniques to yield information-based strategies for decision problems, TQM aims at improving the quality of processes to produce superior products at lower cost. Hence, MS and TQM should, in principle, be intertwined to attain efficient and cost-effective operations. However, neither researchers nor practitioners in these two fields have recognized the vital linkage. By viewing TQM from process-improvement and implementation perspectives, I establish links of prominent MS techniques, such as decision analysis, forecasting, mathematical programming, and simulation, to various facets of TQM. Applications of two important tools (linear programming and simulation) to the service operations of high customer-contact organizations illustrate these linkages. I strongly encourage organizations to systematically integrate MS techniques into TQM programs. Such e...
55 citations
TL;DR: The author proposes a paradigm to train the MBA students to be active modelers by using the personal computer and software, primarily the spreadsheet, that allow significantly faster and easier modeling and also make possible a new style of modeling, referred to as "end-user-modeling."
Abstract: Discussion about the decline in management science in the business schools. The author proposes a paradigm to train the MBA students to be active modelers by using the personal computer and software, primarily the spreadsheet. Those tools allow significantly faster and easier modeling and also make possible a new style of modeling, referred to as "end-user-modeling."
54 citations
TL;DR: In this article, a bid-line generator was used to help Federal Express perform what-if analyses of work rules during contract negotiations with ALPA, the bargaining unit for the company's pilots.
Abstract: We built a bid-line generator to help Federal Express perform what-if analyses of work rules during contract negotiations with ALPA, the bargaining unit for the company's pilots. The objectives were to minimize both the number of bid lines produced a measure of required manning and the amount of flying not assigned to bid lines flying requirements that must be accommodated during subsequent phases of scheduling. The tool was useful in negotiations since it was automated and easily modified in-house to provide quick responses to bid line what-ifs. Using a two-step process, the tool produces a complete set of legal, flyable lines for an airplane fleet and identifies the remaining open unscheduled flying. First it uses simulated annealing to find as many good bid lines as possible; then it uses a greedy heuristic to complete as many more lines as possible.
42 citations
TL;DR: The specialized shift assignment heuristic (SSAH) as mentioned in this paper was developed for assigning telephone operators to shifts at New Brunswick Telephone Company (NBTel) in the early 1970s.
Abstract: I developed a procedure for assigning telephone operators to shifts at New Brunswick Telephone Company (NBTel). Although the problem has received scant attention in the literature, its solution greatly affects employees' satisfaction with their work schedules. NBTel requires that all shifts be assigned to employees, and it is obligated contractually to satisfy preferences for shifts in order of employee seniority. The specialized shift assignment heuristic (SSAH) that I developed runs on a personal computer, generating approximately three solutions per second. Employee and shift databases are maintained in a spreadsheet, and macros are used to integrate the heuristic into the spreadsheet. Both management and employees see SSAH as an improvement over the previous manual procedure.
TL;DR: A course timetabling system for the Anderson School of Management at UCLA is implemented to schedule the core courses using an integer-programming algorithm and second to generate a timetable by using a heuristic algorithm to solve a variant of a quadratic assignment problem.
Abstract: Every school must generate a timetable for its courses. If the number of classes is large—say 100 or more—and constraints and preferences are involved, this problem becomes too time-consuming to do manually. I implemented a course timetabling system for the Anderson School of Management at UCLA. I divided the overall problem into two subproblems: first to schedule the core courses using an integer-programming algorithm, and second to generate a timetable by using a heuristic algorithm to solve a variant of a quadratic assignment problem. The administrators have been using this decision support system over the past three years to schedule the courses every quarter and state that it generates timetables as good as the manual ones but a lot faster.
TL;DR: In this article, the authors developed an efficient optimization-based system for a major US airline to address the problem of generating month-long assignments or bidlines, which takes into account all relevant federal and union regulations and possesses a host of parameters that schedulers use to control the quality of the bidlines generated.
Abstract: Most US airlines generate pairings (or several-days-long work schedules) for airline crews and then string these pairings together into efficient month-long assignments or bidlines. In addition to meeting all relevant federal and union regulations, the generated bidlines must meet unwritten quality-of-life criteria. We developed an efficient optimization-based system for a major US airline to address this problem. It takes into account all relevant federal and union regulations and possesses a host of parameters that schedulers use to control the quality of the bidlines generated. The benefits from the system include reducing the time and resources needed to generate bidlines, improving crew utilization, and the ability to conduct what-if analyses to assess the impact of changes in the work rules and environment.
TL;DR: The citations and selective references over the last two decades or so of Interfaces to obtain a snapshot of where the field has been and where it is heading.
Abstract: Many leading OR professionals think that our primary mission should be to apply the mathematical and scientific principles of OR to real-world problems rather than to pursue theoretical research. To encourage the application of OR models, in 1976 the editors of Interfaces shifted the emphasis of the journal from meta research to applications and survey papers. I analyzed the citations and selective references over the last two decades or so of Interfaces to obtain a snapshot of where the field has been and where it is heading. I analyzed 1,294 articles, 2,190 authors, and more than 2,500 references.
TL;DR: Accurate measurement of the cost of regulation is the first step to better regulatory practice, which means accounting for the regulatory burdens on firms and subordinate governments and allocating those burdens to the regulatory policies that induced them.
Abstract: Advocates of regulatory benefit-cost analysis are right in theory, albeit somewhat impractical In a sense, they have put the cart before the horse Right now we cannot satisfactorily estimate the costs of government regulation, let alone its benefits We must understand what drives cost before we can make satisfactory cost estimates But, first of all, we need good cost measures to figure out what drives cost We don't now measure the costs of regulation Accurate measurement of the cost of regulation is, therefore, the first step to better regulatory practice This means accounting for the regulatory burdens on firms and subordinate governments and allocating those burdens to the regulatory policies that induced them
TL;DR: The Federal Express Corporation has used OR to help make its major business decisions since its overnight package delivery operations began in 1973 as discussed by the authors, and a successful origin-destination model followed by models to simulate operations, finances, engine use, personal assignments, and route structures influenced the conduct of business during periods of substantial growth.
Abstract: Federal Express Corporation has used operations research OR to help make its major business decisions since its overnight package delivery operations began in 1973. An early failure pointed out the need for scientific analysis. Subsequently, a successful origin-destination model followed by models to simulate operations, finances, engine use, personal assignments, and route structures influenced the conduct of business during periods of substantial growth. There were many false starts between the successes. CEO and founder Frederick W. Smith played a central role in the use of OR at the company: he established a relationship with OR and management science personnel and this relationship supported the growth and success of the company.
TL;DR: The authors argue that the course's success is due largely to its focus on managerial relevance, rather than operations research, management science, statistics, or any other methodological discipline, per se.
Abstract: OR/MS has come under increasing pressure within the MBA community to justify its place in the curriculum. Bucking this trend, Darden's first-year OR/MS course, “Quantitative analysis” (QA), is routinely rated by students as one of the top courses in the required core of the MBA curriculum. We believe the course's success is due largely to its focus on managerial relevance, rather than operations research, management science, statistics, or any other methodological discipline, per se. By managerial relevance, we mean that our modules and individual classes have a decision-oriented focus, raise issues and address contexts pertinent to the informed business person, and integrate closely with functional courses like finance, marketing, and operations. We contend that managerial relevance depends less on the macro-level course design than on the details at the class- and module-design levels.
TL;DR: TIMS was founded December 1, 1953 at a meeting held at Columbia University in the City of New York as mentioned in this paper, and the TIMS' 40th anniversary was celebrated in 2013.
Abstract: TIMS was founded December 1, 1953 at a meeting held at Columbia University in the City of New York. I wrote this report in commemoration of TIMS' 40th anniversary and to answer such questions as, What were the origins of TIMS? What led up to the founding of TIMS? What were its original purposes? Who were its originators? What were their motivations? Have its founding purposes been fulfilled? Is there any valuable hindsight to be gained?
TL;DR: In this article, the authors implemented integer programming to help SSLPG decide on the locations and long run sizes of its bottling plants, and estimated that the recommended configuration of bottling plant is about $1 million cheaper annually than the one that SSLPG had initially planned.
Abstract: Shri Shakti LPG Ltd. (SSLPG) imports and markets propane (referred to as liquefied petroleum gas (LPG) in India) in south India. It sells LPG in packed (cylinder) form to domestic customers and commercial establishments through a network of dealers. Dealers replenish their stocks of filled cylinders from bottling plants, which in turn receive LPG in bulk from the cheaper of SSLPG's two import-and-storage facilities that are located on the Indian coast. We implemented integer programming to help SSLPG decide on the locations and long-run sizes of its bottling plants. We estimate that our recommended configuration of bottling plants is about $1 million cheaper annually than the one that SSLPG had initially planned.
TL;DR: A hierarchical value model is developed based on Department of Defense policy documents and the operational judgments of Air University faculty and students senior and mid-level managers who will be future Air Force leaders to determine the technologies whose advancement will do the most to make the high-priority systems a reality.
Abstract: In a major Air Force study of future space systems, SPACECAST 2020, study teams produced a set of system concepts for 21st century military space operations. Our goal was to assess the potential operational utility of these systems in an objective, traceable, and robust manner, so that we could compare the systems and identify the most important. An additional goal was to determine the technologies whose advancement will do the most to make the high-priority systems a reality. To do this, we developed a hierarchical value model based on Department of Defense policy documents and the operational judgments of Air University faculty and students senior and mid-level managers who will be future Air Force leaders. We completed the study within an extremely tight deadline, and it was widely accepted within the Air Force.
TL;DR: In this article, the authors discuss many principles of creative thinking and ways in which you can become more creative and enhance your problem-solving skills, and invite readers to submit their examples, comments, and perspectives on creativity.
Abstract: Over the years, Gene Woolsey and others have taught us that mathematics and models are not always necessary to solve important problems in OR/MS. Often the best solutions are novel and unusual—that is, they are creative. The principles of creative thinking can help practitioners and researchers in OR/MS explain, understand, and enhance their work. In this series of columns, I discuss many principles of creative thinking and ways in which you can become more creative and enhance your problem-solving skills. I invite you to submit your examples, comments, and perspectives on creativity.
TL;DR: In this article, a decision support system for investment projects in pollution abatement plants at state-owned copper smelters in Chile is developed to determine the optimal investment policy for this interrelated production-environmental problem.
Abstract: We developed a decision-support system for investment projects in pollution abatement plants at state-owned copper smelters in Chile. We formulated a mixed-integer linear model to determine the optimal investment policy for this interrelated production-environmental problem. Because of the significant differences between the model's solutions and the initial clean-up plans the smelters submitted to the environmental authorities, the government has revised the smelters' clean-up plans, initially working to obtain more complete and reliable information. Furthermore, it has put some of the projects presented in the original clean-up plans on hold until it has a refined version of the model. The Chilean budget director has approved other clean-up plans because, as the director of policy planning at Cochilco said, they are consistent with the model's recommendations.
TL;DR: The development of indices of health care needs based on empirical hospital utilization data demonstrated that scientific management methods can have a profound impact at a high level of national policy.
Abstract: The British National Health Service delivers the great majority of the country's health care. One of the key policy problems confronting the organization is how its funds should be allocated to different parts of the country. We developed indices of health care needs based on empirical hospital utilization data. The national government now uses the indices as the basis for allocating a large part of NHS funds to health authorities. Moreover, the success of the project has encouraged the government to seek to introduce needs indices for the entire NHS budget, and the study team is now extending the area of application to the broader public sector. The study has therefore demonstrated that scientific management methods can have a profound impact at a high level of national policy.
TL;DR: In this article, a generic simulation model is developed to help design and operate a multimillion-dollar batch-process chemical facility, which is used to identify throughput issues related to new plant designs and to evaluate proposed improvements prior to implementation, thus saving considerable cost and time.
Abstract: Operating a batch-processing chemical-plant efficiently is difficult. Chemical processes require specialized equipment that is sensitive to precise operating conditions and subject to strict quality conformance. Chemical formulations having unique attributes require the simultaneous use of multiple resources to process and move products through the plant. One of our clients used a generic simulation model we developed to help design and operate a multimillion-dollar batch-process chemical facility. Our client used the model to evaluate the impact of many complex issues—such as scheduling policy, inventory policy, resource sizing and configuration, operator schedules, and processing capability—for a proposed process facility. The client used the model to identify throughput issues related to new plant designs and to evaluate proposed improvements prior to implementation, thus saving considerable cost and time.
TL;DR: In this paper, a mixed-integer programming model was used to support the integrated municipal solid waste management plan and implementing the strategy in several South Carolina counties; however, they encountered a number of problems in moving the optimal solution into the decision-making process.
Abstract: Constructing an integrated municipal solid waste management plan and implementing the strategy is becoming increasingly important. We constructed a mixed-integer programming model to support this planning effort in several South Carolina counties; however, we encountered a number of problems in moving the optimal solution into the decision-making process. Most of these problems emanated from the fact that people making policy decisions know that many factors must be considered that are not part of an economic model. We discovered that understanding the decision-making process was key to having the optimal solution used during planning. This understanding led us to construct a spreadsheet-based model to serve as an interface between the optimization model and the decision makers. As such, the planning effort was greatly enhanced by the information contained in the optimization model, but it included all the other factors that are important to communities but are not modeled. We provide the actual results f...
TL;DR: In this paper, a joint SANDF and Deloitte and Touche team supported the joint strategic management process (JSMP) with OR/MS based decision support models, and the results indicated clear opportunities for major additional savings.
Abstract: In January of 1994, the chief of the South African National Defense Force (SANDF) asked the question: “In the absence of a conventional military threat, what should the size and shape of the SANDF be?” A joint SANDF and Deloitte and Touche team supported the joint strategic management process (JSMP) with OR/MS based decision support models. The team created the following models: a risk model of the probability and potential impact of various defense contingencies, a growth model of growth potential of force structure elements, a cost model (zero based), a mixed-integer-programming model of all the relationships, and a manual model allowing the user to select different tasks and strategies. The project resulted in a saving on the approved force design (size and shape) of more than 22 percent. The results indicate clear opportunities for major additional savings.
TL;DR: The OR department at Stanford University has made a 20-year effort to develop an environment for learning the practice of OR as mentioned in this paper, and the first of two courses is based on student teams competing to improve existing case results.
Abstract: The OR department at Stanford University has made a 20-year effort to develop an environment for learning the practice of OR. The first of two courses is based on student teams competing to improve existing case results, and the second course is based on student teams undertaking sponsored projects in industry.
TL;DR: This article constructed linear programming models to identify insolvent traders, to determine the fraction of debt insolvable traders could pay their creditors, and to apportion an insolvent trader's payment to his creditors by asset type.
Abstract: Kuwait's al-Manakh stock market crash in August 1982, which resulted in an outstanding debt of US $94 billion, subjected banks to high risks and precipitated an economic recession, business failures, and bankruptcies. Courts could not settle traders' debts one at a time because of their entanglement. We constructed linear programming models to identify insolvent traders, to determine the fraction of debt insolvent traders could pay their creditors, and to apportion an insolvent trader's payment to his creditors by asset type. The models provided the basis for the final court decisions in resolving the crisis. They proved to be effective, equitable, and robust. Without this work, courts would have been occupied for years with the criminal, commercial, and bankruptcy cases resulting from 29,000 postdated checks; it avoided more than $10 billion in court costs and attorney fees.
TL;DR: AT&T Capital as discussed by the authors designed three sets of decision automation systems and the associated decision strategies for front-end credit decisions, life-cycle credit line management, and delinquent account collections.
Abstract: AT&T Capital Corporation, the largest publicly held leasing and financing company in the US, owns and manages over $12 billion in assets In 1992, we began work to enhance the viability and profitability of its small-ticket business We designed three sets of decision automation systems and the associated decision strategies for front-end credit decisions, life-cycle credit-line management, and delinquent account collections The majority (73 percent) of the credit-granting decisions in AT&T Capital's small-ticket business are now made automatically, including $685 million in new transactions annually Productivity gains have enhanced competitiveness by reducing response times and increased profitability by reducing credit and collections operating costs by over $31 million annually Finally, improvements in decision quality have led to business volume gains of $86 million annually, while reducing bad debt losses by $11 million annually
TL;DR: The second part of the author's discussion of creative problem-solving techniques covering problem finding, idea finding, solution finding, and acceptance finding is presented in this article, where the authors discuss the importance of acceptance finding.
Abstract: The second part of the author's discussion of creative problem-solving techniques covering problem finding, idea finding, solution finding, and acceptance finding.