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1066. Dynamic Berth Allocation Policies at Deep-sea Terminals
Invited abstract in session MA-29: Combinatorial Optimization models and applications in Logistics and Transportation I, stream Combinatorial Optimization.
Monday, 8:30-10:00Room: 157 (building: 208)
Authors (first author is the speaker)
| 1. | Orkun Tunay
|
| Erasmus University | |
| 2. | Pieter van den Berg
|
| Rotterdam School of Management, Erasmus University | |
| 3. | Rob Zuidwijk
|
| Technology Operations Management, RSM Erasmus University | |
| 4. | Debjit Roy
|
| Production and Quantitative Methods, Indian Institute of Management Ahmedabad |
Abstract
While deep-sea vessels play an important role for the revenue streams of container terminals, barges and feeders play an important role in ensuring the functioning of the transshipment and hinterland transportation operations. Besides, the roles of feeders and barges are further leveraged as a cost and emission-efficient alternative to long-haul trucking. These different classes of vessels compete for the same berth space in container terminals. The terminal operators conventionally have the tendency to fully prioritize deep-sea vessels. However, with the increasing incentives and regulatory pressure for the increase of barge and feeder throughput, some terminal operators started to allocate dedicated berths for barges and feeders. In this paper we will study the berth allocation problem in order to find a pareto-optimality frontier that balances barge throughput and deep-sea vessel waiting times. Barges and feeders which are of smaller volume, occupy a smaller space and have a shorter expected handling time. By using analytical methods from Queuing Theory, we will first demonstrate the pareto-efficiency of different heuristics of berth allocation policies, i.e. dedicated terminal spaces, barge limits, motivated by the current industry practices. Based on the insights that we receive from analytically tractable systems, we will design a Markov Decision Process to propose a better pareto-optimality frontier with dynamic policies.
Keywords
- Transportation
- Stochastic Models
- Logistics
Status: accepted
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