-
Conferences/Talks
| INFORMS
Annual Meeting, San Francisco, Nov 13-16, 2005 |
||
|
|
||
| Cluster: | Optimization/ Optimization and Data Mining | |
|
|
||
| Session Information: | Wednesday Nov 16, 15:30 - 17:00 | |
|
|
||
| Title: | Diagnosis Models for Port of Entry Inspections | |
| Chair: | Endre Boros, Professor, Rutgers University,
RUTCOR,
640 Bartholomew Road, Piscataway NJ 08854, United States,
boros@rutcor.rutgers.edu |
|
|
|
||
| Abstract Details | ||
|
|
||
| Title: | Modeling Cargo Flow Security Operations in Marine Ports | |
| Lead: | Tayfur
Altiok, Professor, Rutgers University, Department of Industrial
Engineering, Piscataway NJ 08854, United States, altiok@rci.rutgers.edu |
|
| Co-Author: | Kevin Saeger, Los Alamos National Laboratory, LANL, Los Alamos NM 87545, United States, saeger@lanl.gov | |
| Benjamin
Melamed, Rutgers University, 94 Rockafeller Road, Piscataway NJ
08854, United States, MELAMED@RBS.RUTGERS.EDU |
||
| Abstract: | We model cargo security operations in a container port including handling, storage and inspection. Here, vessel arrival processes, vessel unloading operations and the inspection process are critical modeling components. The impact of the arrival process and the inspection ratio on the overall marine port operation will be discussed. | |
| Title: | Decision Support Algorithms for Port-of-Entry Inspection | |
| Lead: | Fred
S. Roberts, Rutgers University, DIMACS, 96 Frelinghuysen Rd,
Piscataway NJ 08854, United States, froberts@dimax.rutgers.edu |
|
| Co-Author: | Phillip D. Stroud, Los Alamos National Laboratory, Mail Stop F607, Los Alamos NM 87545, United States, stroud@lanl.gov | |
| Abstract: | We describe approaches to efficiently discover smuggling attempts at U.S. ports of entry. We use a sequential decision making model: Containers are routed to different tests depending on outcomes of earlier tests. We describe ways to find inspection schemes minimizing cost, including "cost" of false positives and negatives. | |
| Title: | Optimum
Inspection
Strategies for Port Entry Containers |
|
| Lead: | Elsayed
Elsayed, Rutgers
University, Department of Industrial and Systems Eng, 96 Frelinghuysen
Road, Piscataway NJ 08854, United States, elsayed@rci.rutgers.edu |
|
| Co-Author: | Christina Schroepfer, Graduate Assistant, Rutgers University, Department of Industrial and Systems Eng, 96 Frelinghuysen Road, Piscataway NJ 08854-8018, United States, cms168@rci.rutgers.edu | |
| Phillip
D. Stroud, Los Alamos National Laboratory, Mail Stop F607, Los
Alamos NM 87545, United States, stroud@lanl.gov |
||
| Hao
Zhang, Graduate
Assistant, Rutgers University, Department of Industrial and Systems
Eng, 96 Frelinghuysen Road, Piscataway NJ 08854-8018, United States,
haoz@email.eden.rutgers.edu |
||
| Abstract: | We develop a network optimization type linear programming model for sequential container inspection. In this model we determine optimum routing and inspection sequence as well as the optimum sensors threshold levels that minimize the total "cost", including expenses arising from storage, inspection and delays, as well as the estimated cost incurred by false positives and negatives. | |
| Title: | OR Models for
Finding Optimal Container Inspection Strategies |
|
| Lead: | Endre Boros, Professor, Rutgers University, RUTCOR, 640 Bartholomew Road, Piscataway NJ 08854, United States, boros@rutcor.rutgers.edu | |
| Co-Author: | Liliya Fedzhora, Rutgers University, 640 Bartholomew Road, Piscataway NJ 08854, United States, fedzhora@rutcor.rutgers.edu | |
| Paul
B. Kantor, Rutgers University, 4 Huntington St., New Brunswick NJ
08904, United States, kantor@scils.rutgers.edu |
||
| Phillip
D. Stroud, Los Alamos National Laboratory, Mail Stop F607, Los
Alamos NM 87545, United States, stroud@lanl.gov |
||
| Abstract: | We develop a network optimization type linear programming model for sequential container inspection. In this model we determine optimum routing and inspection sequence as well as the optimum sensors threshold levels that minimize the total "cost", including expenses arising from storage, inspection and delays, as well as the estimated cost incurred by false positives and negatives. | |