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We investigate the impact of delay announcements on the coordination within hospital networks using a combination of empirical observations and numerical experiments. We offer empirical evidence that suggests that patients take delay information into account when choosing emergency service providers and that such information can help increase coordination in the network, leading to improvements in the performance of the network, as measured by emergency department wait times. Our numerical results indicate that the level of coordination that can be achieved is limited by the patients' sensitivity to waiting, the load of the system, the heterogeneity among hospitals, and, importantly, the method hospitals use to estimate delays. We show that delay estimators that are based on historical averages may cause oscillation in the system and lead to higher average wait times when patients are sensitive to delay. We provide empirical evidence that suggests that such oscillations occur in hospital networks in the United States. This paper was accepted by Gad Allon, operations management. [ABSTRACT FROM AUTHOR]

Hub networks play an important role in many transportation and telecommunications systems. This paper introduces a new model called the hub arc location model. Rather than locate discrete hub facilities, this model locates hub arcs, which have reduced unit flow costs. Four special cases of the general hub arc location model are examined in detail. We provide motivation for the new models, and present examples and optimal solutions, using data for U.S. air passenger traffic. Results are used to compare optimal costs, hub locations, and hub arc locations with corresponding hub median optimal solutions. The results reveal interesting spatial patterns and help identify promising cities and regions for hubs. A companion paper (Campbell et al. 2005) presents integer programming formulations and solution algorithms for the new hub arc problems. It also provides details and computation times for these solution algorithms. [ABSTRACT FROM AUTHOR]

This paper discusses a computer-assisted method for routing and scheduling street sweepers in a municipality. We present the basic structure of this vehicle routing and scheduling problem, formulate the street-sweeper routing problem, and explain the algorithm. The computer implementation based on this algorithm is then described. Computational experience with the system in New York City and Washington, D.C., is presented and the obstacles to and successes with implementation are discussed. [ABSTRACT FROM AUTHOR]

This paper, motivated by the experiences of a major U.S.-based broadcast television network, presents algorithms and heuristics to schedule commercial videotapes. Major advertisers purchase several slots to air commercials during a given time period on a broadcast network. We study the problem of scheduling advertiser's commercials in the slots it purchased when the same commercial is to be aired multiple times. Under such a situation, the advertisers typically want the airings of a commercial to be as evenly spaced as possible. Thus, our objective is to schedule a set of commercials in a set of available slots such that multiple airings of the same commercial are as evenly spaced as possible. A natural formulation of this problem is a mixed-integer program that can be solved using third-party solvers. We also develop a branch-and-bound algorithm based on a problem-specific bounding scheme. Both approaches fail to solve larger problem instances within a reasonable time frame. We present an alternative mixed-integer program that lends itself to an efficient solution. For solving even larger problems, we present multiple heuristics. [ABSTRACT FROM AUTHOR]

Congestion in air traffic networks is a serious problem and has received a lot of attention both from the aviation authorities (Federal Aviation Administration, Eurocontrol, etc.) and from the scientific research community. In past years, one way of reducing the amount of congestion has been the adoption of ground holding policies, i.e., a ground hold is imposed to selected aircraft, prior to their departure, so that congestion may be smoothed away. Many airlines in the United States have been complaining about these policies and are pushing toward the new concept of "free flight," where the airlines are almost "free" to choose for each of their flights, when to depart, which route to follow, at what speed, etc., as long as the arrival at the destination airport matches a given time, decided by a central authority (the Federal Aviation Administration in the United States). In this new perspective, to avoid congestion, or at least to reduce it, the central authority has to schedule the arrival times of all flights, with possible delays for some of them. In this paper, we describe an exact algorithm, based on the integration of a heuristic algorithm with an integer linear programming model. This approach provides exact solutions in a much shorter computation time than previous algorithms proposed in the literature. We will report on our computational experiences using large instances based on actual Official Airline Guide data for the United States air traffic network. [ABSTRACT FROM AUTHOR]

Service options for the electric utility industry are increasingly including provisions to dynamically dispatch prices or service interruption calls to customers. When the number of such calls is contractually limited, then the issue of optimally dispatching the calls must be addressed. In this paper, an algorithm for optimally dispatching interruptible and curtailable (I/C) service options is developed within a stochastic dynamic programming (SDP) framework. The solution yields thresholds for calling load curtailments as a function off 1)the number of days remaining in the period, 2) the available number of interruptions, and 3) the level of uncertainty regarding future price and cost fluctuations. The SDP approach also provides a framework for optimally designing the I/C program parameters. An illustration of the dispatching routine is provided using data from Niagara Mohawk Power Corporation (NMPC). The algorithm developed in the paper is currently being employed by NMPC as part of its I/C program for industrial and commerical customers. [ABSTRACT FROM AUTHOR]

The equilibrium network design problem can be formulated as a mathematical program with variational inequality constraints. We know this problem is nonconvex; hence, it is difficult to solve for a globally optimal solution. In this paper we propose a simulated annealing algorithm for the equilibrium network design problem. We demonstrate the ability of this algorithm to determine a globally optimal solution for two different networks. One of these describes an actual city in the midwestern United States. [ABSTRACT FROM AUTHOR]

Roth and Rothblum [Roth, A. E., U. G. Rothblum. 1999. Truncation strategies in marching markets--In search of advice for participants. Econometrica 67 21-43] showed that for matching markets using the deterred acceptance algorithm a physician with symmetric (incomplete) information possibly gains only by truncating her true ranking We show that symmetric information environments this result is identical for all priority mechanisms and all linear programming mechanisms introduced in British entry-level medical markets and in public school choice in some American cities. [ABSTRACT FROM AUTHOR]

The airline crew scheduling problem is the problem of assigning crew itineraries to flights. The problem is hard due to a large number of itineraries and the complicated cost function of an itinerary. The classic approach, which uses a set partitioning formulation, only captures the objective function of minimizing cost. We add a second goal of maximizing the repetition or regularity of itineraries over a weekly horizon and we develop models that capture regularity. We present a new algorithm that solves the crew scheduling problem over a weekly horizon. Solutions are reported that improve on existing solutions used by an airline. [ABSTRACT FROM AUTHOR]

To understand how greatly new computer-based Decision Support Systems can benefit air traffic control, we study air traffic delays for landing aircraft at Boston. First, we develop an empirical model for present day Landing Time Intervals (LTIs) between aircraft in terms of two factors that significantly affect them: the landing runway configuration and the weight-class categories of the aircraft. Next, we develop three increasingly rich models of Boston's terminal airspace and apply, on airflow data, sequencing algorithms meant to expedite the landing of incoming aircraft. Comparing sequences suggested by the algorithms to those now used by controllers, we estimate that better sequencing can reduce delays by 30% in some instances. However, such improvements must be balanced against the effects such algorithms would have on workloads and other aspects of the air traffic control environment. [ABSTRACT FROM AUTHOR]

The article presents a solution to a large-scale traveling-salesman problem which shows that a certain tour of 49 cities, one in each of the 48 states and Washington, D.C., has the shortest road distance. A brief history of the problem is provided. A city in each state including the District of Columbia was selected to try the optimal path method on a large problem. The devices in obtaining solutions include the use of undirected tours, the imposition of linear conditions to characterize the tours, the speeding up of the iterative process and the use of a combinatorial approach.

The scientific exploration of the moon requires that a number of experiments be conducted for the purpose of investigating the many questions and hypotheses posed by nearly every discipline in the scientific community. The broad interest in this effort, the limitations of time and resources for conducting the program, and the complex engineering constraints imposed by the logistics systems justify the development of an effective method of making optimum selection of experiments according to the most meaningful criteria. The developed method provides a determination of alternate optimum solutions from which scientific authority may choose. Basic lunar scientific objectives, as determined by NASA interdisciplinary panels, serve as inputs to the system. The relative worth of each objective according to scientific merit is determined by a stratified, intradisciplinary sample of the scientific community using a modified majority-rule technique. The experiments are then ordered according to their contribution to the ordered objectives. A subjective programming method provides alternate payload choices that optimize the scientific merit of the experiments within the engineering constraints of a lunar payload. An example is presented that simulates the use of an algorithm for selecting an optimism experiment payload. [ABSTRACT FROM AUTHOR]

This article informs that the Damage Limiting Study was conducted circa 1963-1964 at the direction of Harold Brown under the general guidance of the Secretary of Defense, Robert McNamara. The mandate was straightforward: What are the prospects of limiting damage to the United States from a determined attack by Soviet ICBMs and Soviet bombers equipped with nuclear weapons? Based on this illumination and other factors, the Secretary of Defense decided that striving to limit damage in any meaningful sense against a determined and reactive Soviet attack was not a viable strategy, and proceeded accordingly. Three analysts undertook to incorporate an algorithm into SABER GRAND so that the computer could act as the brilliant commander for both sides. Acting as a brilliant commander meant the algorithm allocates the weight of effort over time among the four tasks so as to maximize the outcome after a stated number of days--and the reverse for the Red Commander. The principal use of the model was to gain insight about the relative merits of alternative investment packages.

The article discusses the use of linear programming in U.S. industry. Three aspects of the application of linear programming are presented, including model building, mathematics, and computation. Many real-world industry cases have been related to finding the most economical way of transporting materials between various sources and destinations, and have been solved by special algorithms. In the mathematics of linear programming there are four main areas of research, including computational techniques that take advantage of special features of problems, methods of performing sensitivity analyses for the coefficients of the problem, methods that relate to dynamic problems, and stochastic techniques for handling uncertainty.

This article is based on a talk given at the 1988 TIMS/ORSA meeting in Washington, D.C., about developments since the 1974 Lanchester Prize was awarded to P. J. Kolesar and W. E. Walker in 1974, for a paper that described an algorithm for dynamically repositioning available fire companies in response to changing patterns of availabilities. The life history of that algorithm motivates a vision for the future of the applied side of the OR profession. [ABSTRACT FROM AUTHOR]