Tug & Pilot Assignment Scheduling Problem
The Tug & Pilot Assignment Scheduling Problem (TPASP) determines how pilots and tugboats are allocated to vessels for inbound, shifting, and outbound movements. Assignments must satisfy vessel size/draft requirements, pilot qualifications, tidal and channel constraints, tug power limits, and real-time operational changes. Objectives include reducing vessel delays, improving resource utilization, minimizing fuel use, and ensuring fair workload distribution among pilots.
Scheduling Focus
Objective
- Minimize vessel waiting times at anchorage and departure delays.
- Maximize tug and pilot utilization while reducing idle repositioning.
- Reduce emissions and fuel use during tug operations and vessel idle periods.
Decision Variables
- Assignment of pilot(s) and tug(s) to each vessel movement (arrival, shifting, departure).
- Start and end times for tug assist and pilot service, including repositioning routes.
- Choice of tug class (bollard pull) and pilot qualification category per vessel.
Constraints
- Tug power and number requirements per vessel class and maneuver type.
- Pilot duty time limits, availability, and qualification matching.
- Tidal and channel capacity restrictions; safe vessel separations.
Data Sources
- Vessel ETA/ETD data, tidal tables, channel restrictions, and berth plans.
- Tug fleet database: power, base locations, speeds, fuel/emission profiles.
- Pilot rosters with shift times, licenses, and historical assignment records.
Main Assumptions
- Planning horizon typically covers 12–48 hours and updates dynamically with ETA shifts.
- Each tug/pilot handles one task at a time, including reposition and standby times.
- Scenario-based or stochastic variants model arrival uncertainty and tidal variation.
- Safety rules and qualification matching strictly enforced for every allocation.
Modeling Approaches
The Tug & Pilot Assignment Scheduling Problem is often formulated as a Mixed-Integer Linear Program (MILP) or multi-objective model, sometimes extended with simulation and heuristics for real-time rescheduling.
- MILP/Exact: Channel-constrained vessel scheduling integrating pilot and tug assignment (Abou Kasm & Diabat 2021).
- Fuzzy/Game-Theoretic: Stackelberg or bi-level approaches under uncertainty for balancing reliability and cost.
- Heuristics & Metaheuristics: Large-scale or real-time variants using GA, VNS, and hybrid co-scheduling with berth planning.
Reference Studies
🧭 Academic Foundations
| Study | Key Findings |
|---|---|
| Equitable Vessel Traffic Scheduling in a Seaport | Instance files used to schedule vessel traffic and pilots. The set includes port layout, vessel and pilot data structures. |
| APM Terminals – Truck Appointments & Operations API | Data feeds operational movements to reconstruct tug/pilot demand timelines adjacent to berth windows (registration needed). |
| Port of Virginia – API | API for gate/operations. Useful to build real time series around arrivals/departures and derive pilot/tug demand patterns around channel windows (registrations needed). |
⚙️ Industry Applications
| Case / Service | Description |
|---|---|
| Scheduling Tugboats in a Seaport | Tugboat scheduling benchmark instances plus sample solutions (multiple scales, vessel/tug parameters). |
| LOS ONE companion data | Supplemental XLSX base data used in tugboat scheduling simulations. |
Real operational datasets are rarely public, but the cited studies document realistic parameters and measurable efficiency gains.