The in-Port vessel Scheduling and tug Assignment Problem (PSAP) aims at determining the schedule for a given set of vessel movements, and their escorting tugs within a port. In this paper, we propose, compare and discuss models and algorithms for determining solutions for the PSAP. Specifically, we introduce two mathematical programming models and we derive from them four heuristics: two based on the time limited execution of a commercial solver, and two on a receding horizon principle. Finally, we present the results of a computational study aiming at assessing the performance of the considered algorithms on problem instances obtained from the Port of Venice, a medium size Italian port. The receding horizon based heuristics show good performances. They provide good quality solutions for the majority of the instances within a reasonable computational time.
Models and algorithms for an integrated vessel scheduling and tug assignment problem within a canal harbor
Raffaele Pesenti
2022-01-01
Abstract
The in-Port vessel Scheduling and tug Assignment Problem (PSAP) aims at determining the schedule for a given set of vessel movements, and their escorting tugs within a port. In this paper, we propose, compare and discuss models and algorithms for determining solutions for the PSAP. Specifically, we introduce two mathematical programming models and we derive from them four heuristics: two based on the time limited execution of a commercial solver, and two on a receding horizon principle. Finally, we present the results of a computational study aiming at assessing the performance of the considered algorithms on problem instances obtained from the Port of Venice, a medium size Italian port. The receding horizon based heuristics show good performances. They provide good quality solutions for the majority of the instances within a reasonable computational time.File | Dimensione | Formato | |
---|---|---|---|
PetrisPellegriniPesenti-Revised_210914Rp.pdf
non disponibili
Descrizione: Pre-print dell'autore
Tipologia:
Documento in Pre-print
Licenza:
Accesso chiuso-personale
Dimensione
1.46 MB
Formato
Adobe PDF
|
1.46 MB | Adobe PDF | Visualizza/Apri |
I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.