Computers & Industrial Engineering | Vol.144, Issue. | 2020-05-31 | Pages 106450
A computational comparison of cargo prioritization and terminal allocation problem models
Inland waterway disruptions may interrupt barge navigation, resulting in significant economic and environmental consequences. Disruption response reroutes disrupted barges to accessible terminals to offload cargo water to land transportation. We investigate how to redirect disrupted barges and prioritize offloading at terminals to minimize the total cargo value loss during inland waterway disruption response. This problem is known in the literature as the cargo prioritization and terminal allocation problem (CPTAP). Previous studies formulated the CPTAP as a non-linear integer programming (NLIP) model, which was solved with a genetic algorithm (NLIPGA) and a tabu search (NLIPTS) approach. In this article, we formulate CPTAP as a mixed integer linear programming (MILP) model and improve its performance through the addition of valid inequalities, which we refer to as MILP’. Due to problem complexity, the NLIPGA and NLIPTS results were validated for small size instances. We fill this gap by using the lower bounds of MILP’ model to validate the quality of NLIPGA and NLIPTS solutions, and we compare the MILP’ with the NLIPGA and the NLIPTS solutions for multiple scenarios. The MILP’ formulation is found to outperform the NLIPGA and NLIPTS approaches by reducing the total cargo value loss.
Original Text (This is the original text for your reference.)
A computational comparison of cargo prioritization and terminal allocation problem models
Inland waterway disruptions may interrupt barge navigation, resulting in significant economic and environmental consequences. Disruption response reroutes disrupted barges to accessible terminals to offload cargo water to land transportation. We investigate how to redirect disrupted barges and prioritize offloading at terminals to minimize the total cargo value loss during inland waterway disruption response. This problem is known in the literature as the cargo prioritization and terminal allocation problem (CPTAP). Previous studies formulated the CPTAP as a non-linear integer programming (NLIP) model, which was solved with a genetic algorithm (NLIPGA) and a tabu search (NLIPTS) approach. In this article, we formulate CPTAP as a mixed integer linear programming (MILP) model and improve its performance through the addition of valid inequalities, which we refer to as MILP’. Due to problem complexity, the NLIPGA and NLIPTS results were validated for small size instances. We fill this gap by using the lower bounds of MILP’ model to validate the quality of NLIPGA and NLIPTS solutions, and we compare the MILP’ with the NLIPGA and the NLIPTS solutions for multiple scenarios. The MILP’ formulation is found to outperform the NLIPGA and NLIPTS approaches by reducing the total cargo value loss.
+More
disrupted barges and prioritize offloading nlipga and nlipts approaches total cargo value economic and environmental consequences disruption response cptap barge inland waterway disruption genetic algorithm mixed integer linear programming milp model lower bounds of milp model milp formulation cargo prioritization and terminal allocation problem inequalities tabu search nlipts
Select your report category*
Reason*
New sign-in location:
Last sign-in location:
Last sign-in date: