Freight Container Loading Optimization Through 2D Layer Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for freight container loading are inefficient, relying heavily on manual calculations and spreadsheets, and are computationally expensive, making them unsuitable for daily operational planning.
Innovation Solution
A computer-based system utilizing heuristic algorithms and integer programming optimization models to optimize the placement of objects within 3-dimensional spaces, such as gaylords and trucks, by defining 2-dimensional layers and assigning objects within these layers to maximize space utilization and minimize the number of containers needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computational heuristic methods are used to solve the 3-D container loading problem, then loading optimization is achieved, but computational cost and time consumption increase excessively
Solution Approach 1:
The patent segments the 3-D container loading problem into multiple 2-D layer problems. Each layer is processed independently using optimization algorithms, which reduces the computational complexity from solving a single complex 3-D problem to solving multiple simpler 2-D problems. This segmentation enables efficient optimization while controlling CPU time consumption.
Solution Approach 2:
The patent transforms the 3-D container loading problem into a series of 2-D layer problems. By slicing the three-dimensional space into horizontal layers, the problem dimensionality is reduced, making it computationally tractable for daily operational planning while maintaining optimization effectiveness.
2Ease of operation
If manual calculations and spreadsheets are used for container loading, then ease of operation is maintained, but loading optimization and space utilization are insufficient
Solution Approach 1:
The system performs self-service optimization by automatically calculating the best loading configurations using mathematical models and algorithms. The computer system independently solves the optimization problem without requiring manual intervention, achieving both ease of operation (users simply input data) and high space utilization efficiency.
Solution Approach 2:
The patent replaces manual mechanical calculation processes with automated computer-based optimization systems. The mathematical models and algorithms substitute for manual spreadsheet calculations, enabling the system to handle complex optimization problems that would be impractical to solve manually while maintaining user-friendly operation.
3Productivity
If existing computational methods are used for container loading optimization, then loading efficiency improves, but the complexity of the system increases
Solution Approach 1:
The patent reduces system complexity by segmenting the 3-D loading problem into multiple 2-D layer problems. This decomposition allows the use of simpler, well-established 2-D optimization algorithms rather than complex 3-D algorithms, making the overall system more manageable and easier to implement while maintaining high loading efficiency.
Data Source
AI summary
An analytical method to optimize gaylord building and truck loading for outbound container shipments includes defining, within the 3-dimensional physical space, one or more 2-dimensional layers, each 2-dimensional layer having a fixed height. Using one or more heuristic algorithms, for each of the one or more 2-dimensional layers, one or more objects of a plurality of objects can be assigned for placement within the two-dimensional layer, and one or more placement positions within the 2-dimensional layer can be assigned for each of the one or more of the plurality of objects. The assigned placement positions can be displayed, reported, or otherwise transmitted to a user or system.