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A Multi-Objective Decision and Analysis Approach for the Berth Scheduling Problem

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Berth scheduling can be described as the resource allocation problem of berth space to vessels in a container terminal. When defining the allocation of berths to vessels container terminal operators set several objectives which ideally need to be optimized simultaneously. These multiple objectives are often non-commensurable and gaining an improvement on one objective often causes degrading performance on the other objectives. In this paper, the authors present the application of a multi-objective decision and analysis approach to the berth scheduling problem, a resource allocation problem at container terminals. The proposed approach allows the port operator to efficiently select a subset of solutions over the entire solution space of berth schedules when multiple and conflicting objectives are involved. Results from extensive computational examples using real-world data show that the proposed approach is able to construct and select efficient berth schedules, is consistent, and can be used with confidence.
Title: A Multi-Objective Decision and Analysis Approach for the Berth Scheduling Problem
Description:
Berth scheduling can be described as the resource allocation problem of berth space to vessels in a container terminal.
When defining the allocation of berths to vessels container terminal operators set several objectives which ideally need to be optimized simultaneously.
These multiple objectives are often non-commensurable and gaining an improvement on one objective often causes degrading performance on the other objectives.
In this paper, the authors present the application of a multi-objective decision and analysis approach to the berth scheduling problem, a resource allocation problem at container terminals.
The proposed approach allows the port operator to efficiently select a subset of solutions over the entire solution space of berth schedules when multiple and conflicting objectives are involved.
Results from extensive computational examples using real-world data show that the proposed approach is able to construct and select efficient berth schedules, is consistent, and can be used with confidence.

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