A multi-objective optimization primary planning model for a POE (Port-of-Entry) inspection

Every year, more than 11 million maritime containers and 11 million commercial trucks arrive in the United States, carrying all types of imported goods. As it would be costly to inspect every container, only a fraction of them are inspected before being admitted into the United States. In this paper, a multi-objective optimization (MOO) model is developed for primary allocation of the scarce inspection resources at a POE, especially a land POE (L-POE). This model minimizes the different costs associated with the inspection process, including those associated with delaying the entry of legitimate imports. The resulting model is exploited in two different ways: One is to construct the efficient frontier of the MOO model or a partial efficient frontier with diversity of the solutions maximized; the other is to evaluate a given inspection plan and provide possible suggestions for improvement. The methodologies are described in detail and a simple case study is provided.