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605. On a Generalization of the Information Collection Problem
Invited abstract in session WA-58: MILPs for Vehicle Routing 2, stream VeRoLog - Vehicle Routing and Logistics.
Wednesday, 8:30-10:00Room: S07 (building: 101)
Authors (first author is the speaker)
| 1. | Esther Jose
|
| Industrial and Systems Engineering, University at Buffalo | |
| 2. | Nastaran Oladzad
|
| Industrial and Systems Engineering, University at Buffalo | |
| 3. | John Becker
|
| University at Buffalo | |
| 4. | Rajan Batta
|
| Industrial and Systems Engineering, University at Buffalo |
Abstract
In today's data-driven world, efficient collection of information is crucial. We generalize this on a graph and propose a model that can be applied to a wide range of information collection problems. To solve an information collection problem on a graph where nodes contain retrievable information within a specific range, we introduce a two-phase approach. In the first phase, we pre-process the graph to determine the information that can be collected by moving through edges of the graph. In the second phase, we use a mixed-integer linear programming (MILP) model to maximize the amount of valuable information collected by traversing the edges of the graph within a given time limit. We provide extensions that can accommodate additional assumptions such as varying speed, information degradation, and threat or detection avoidance. Our model has practical applications for any problem where an agent, sensor, or decision maker is collecting information from a space.
Keywords
- Programming, Mixed-Integer
- Graphs and Networks
- Vehicle Routing
Status: accepted
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