Flexible Berth Allocation via Dynamic Vessel Positioning

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Solution Overview

Problem

Current berth allocation methods are inefficient in optimizing vessel placement and cost management within harbors, as they do not account for flexible arrival times and varying handling requirements, leading to suboptimal use of infrastructure and increased operational costs.

Innovation Solution

The system allows for flexible arrival times and considers vessel-specific attributes and berth-specific equipment by modeling the berth allocation problem as a set partitioning problem, generating berth plans that minimize costs and adhere to constraints such as spatial distance and vessel capacity, using commercial solvers to optimize vessel placement across multiple berths.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional berth allocation methods are used, then infrastructure requirements remain static, but vessel turnaround time and operational efficiency deteriorate due to inability to handle flexible arrival times and varying requirements

Engineering Contradiction:

Improvevessel turnaround timeVSAvoidflexibility to handle varying vessel requirements

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The system dynamically adjusts berth allocation based on real-time vessel arrivals, departure times, and specific requirements. The optimization model continuously re-evaluates and re-assigns berths to vessels, allowing the allocation strategy to adapt flexibly to changing conditions rather than following static pre-allocated schedules

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes key parameters such as arrival time windows, berth assignment, and handling schedules to optimize operational efficiency. By allowing parameters like arrival time to be flexible rather than fixed, the system can find optimal solutions that reduce turnaround time while accommodating various vessel requirements

Inventive Principle:

Principle #35Parameter changes

2Productivity

If harbor infrastructure is expanded to meet increasing vessel competition requirements, then berth capacity increases, but implementation cost and time increase significantly

Engineering Contradiction:

Improveberth allocation efficiencyVSAvoidinfrastructure implementation cost and time

Core Design Contradiction:

ProductivityVSEase of manufacture

Solution Approach 1:

Instead of physically expanding infrastructure, the system optimizes by changing operational parameters such as berth assignment algorithms, scheduling parameters, and resource allocation strategies. This software-based optimization achieves improved productivity without the high costs and time requirements of physical infrastructure expansion

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system creates virtual models and simulations of berth operations to test and optimize allocation strategies before implementation. By using digital twins and optimization algorithms, the harbor can evaluate different scenarios and implement the best strategies without physical trial-and-error

Inventive Principle:

Principle #26Copying

3Reliability

If strict berth allocation constraints are enforced, then infrastructure utilization becomes predictable, but operational flexibility and cost optimization deteriorate

Engineering Contradiction:

Improveberth allocation predictabilityVSAvoidoperational flexibility

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The system maintains reliability through structured optimization frameworks while achieving flexibility by dynamically adjusting allocations within defined constraints. The model balances predictable infrastructure utilization with adaptive response to varying vessel requirements by continuously optimizing within operational boundaries

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS20240021085A1Flexible berth management system

Publication Date: 2024.01.18 SAP SE

AI summary

Systems and methods include determination of a plurality of object berth positions, determination of a first incoming time of a first object, determination of a stay duration of the first object, determination of an incoming stay duration of the first object and an outgoing stay duration of the first object, determination of a plurality of discrete incoming stay intervals of the first object based on the first incoming time and the incoming stay duration, determination of a plurality of discrete outgoing stay intervals of the first object based on the plurality of discrete incoming stay intervals of the first object, the incoming stay duration of the first object and the outgoing stay duration of the first object, and identification of one of the plurality of discrete incoming stay intervals of the first object, a first one of the plurality of object berth positions as an incoming berth position of the first object, one of the plurality of discrete outgoing stay intervals of the first object, and a second one of the plurality of object berth positions as an outgoing berth position of the first object based on values associated with the first object at each of the object berth positions during an incoming stay of the first object and on values associated with the first object at each of the object berth positions during an outgoing stay of the first object.