DIMACS/Los Alamos National Laboratory Partnership on Algorithms for Port-of-Entry Inspection

Information for Project Members







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.
   

Document last modified on March 13, 2006.