Scheduling School Buses

Article Abstract:

In the scheduling situation considered here, we are given a set of routes, each associated with a particular school. A single bus is assigned to each route, picking up the students and arriving at their school within a specified time window. The scheduling problem is to find the fewest buses needed to cover all the routes while meeting the time window specifications. We present two integer programming formulations of the scheduling problem and apply them to actual data from New Haven, Connecticut for two different years, as well as to 30 randomly generated problems. Linear programming relaxations of these integer programs were found to produce integer solutions more than 75 percent of the time. In the remaining cases, we found that the few fractional values can be adjusted to integer values without increasing the number of buses needed. Our method reduces the number of buses needed by about 25 percent compared to the manual solutions developed by the New Haven school bus scheduler. (Reprinted by Permission of Publisher.)

Author: Swersey, A.J., Ballard, W.
Linear programming, Integer programming, Transportation, Analysis, Education Administration Software, Educational administration software, Methods, Routing, Scheduling Applications

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Modeling as constrained problem solving: an empirical study of the data modeling process

Article Abstract:

Existing literature on the behavior of people when constructing a model is quite limited. To address this shortcoming, a study that focuses on data modeling is conducted. Data modeling requires representation of various types of data and their interrelationships. A think-aloud process-tracing methodology is employed to observe the data modeling behavior. Results demonstrate that certain heuristics effectively lessened the complexity of the problem at hand. During the study, the manner by which subjects progressed across levels of abstraction in the problem representation is observed. These findings explain how individuals treat the complexities involved in data modeling. They also indicate that development of systems supporting work at different levels of abstraction and movements among these levels is beneficial.

Author: Srinivasan, Ananth, Te'eni, Dov
Research, Problem solving

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