Name
Abstract | ||
|---|---|---|
The practical utility of optimization technologies is often impacted by factors that reflect how these tools are used in practice, including whether various real-world constraints can be adequately modeled, the sophistication of the analysts applying the optimizer, and related environmental factors (e.g. whether a company is willing to trust predictions from computational models). Other features are less appreciated, but of equal importance in terms of dictating the successful use of optimization. These include the scale of problem instances, which in practice drives the development of approximate solution techniques, and constraints imposed by the target computing platforms. End-users often lack state-of-the-art computers, and thus runtime and memory limitations are often a significant, limiting factor in algorithm design. When coupled with large problem scale, the result is a significant technological challenge. We describe our experience developing and deploying both exact and heuristic algorithms for placing sensors in water distribution networks to mitigate against damage due intentional or accidental introduction of contaminants. The target computing platforms for this application have motivated limited-memory techniques that can optimize large-scale sensor placement problems. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-92695-5_10 | LION |
Keywords | Field | DocType |
approximate solution technique,water distribution networks,significant technological challenge,algorithm design,large-scale sensor placement problem,computational model,limited-memory techniques,large problem scale,problem instance,optimization technology,accidental introduction,target computing platform,sensor placement,limiting factor,heuristic algorithm,computer model | Mathematical optimization,Heuristic,Algorithm design,Computer science,Limiting factor,Distribution networks,Facility location problem,Computational model,Artificial intelligence,Lagrangian relaxation,Machine learning,Sophistication | Conference |
Volume | ISSN | Citations |
5313 | 0302-9743 | 5 |
PageRank | References | Authors |
0.49 | 4 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| William E. Hart | 1 | 1028 | 141.71 |
| Jonathan W. Berry | 2 | 445 | 46.01 |
| Erik Boman | 3 | 8 | 2.92 |
| Cynthia A. Phillips | 4 | 1184 | 123.02 |
| Lee Ann Riesen | 5 | 103 | 5.85 |
| Jean-Paul Watson | 6 | 604 | 47.20 |