Package Position Solver for Container Loading Optimization
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Solution Overview
Problem
The complex task of optimizing package loading within containers for shipping faces challenges such as maximizing space utilization, ensuring balanced weight distribution, and adhering to operational constraints, which existing methods struggle to address efficiently due to the vast number of possible configurations and varying package and container dimensions.
Innovation Solution
A solver is employed to determine the optimal loading arrangement of packages within containers by scoring packages based on priority, revenue, and other factors, and then arranging them to maximize space efficiency while ensuring stability and compatibility, using a three-dimensional representation to visualize the arrangement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual or simple algorithms are used to arrange packages, then the process is easy to operate, but space utilization is poor and computational effort is excessive
Solution Approach 1:
The patent segments the package arrangement problem into multiple sub-problems by dividing packages into different groups based on scoring criteria (priority, revenue, weight, volume). This segmentation allows the solver to handle complex configurations systematically by processing packages in manageable groups rather than attempting to optimize all packages simultaneously, thus reducing computational complexity while improving space utilization.
Solution Approach 2:
The patent applies preliminary action by pre-scoring and ranking packages before the actual arrangement process. Packages are evaluated and assigned priority levels based on multiple factors (priority score, revenue per unit weight, revenue per unit volume) in advance. This preliminary classification guides the subsequent packing process, enabling the solver to make informed decisions about package placement without having to evaluate all possible configurations from scratch, thereby reducing computational effort while optimizing space usage.
2Productivity
If packages are arranged to maximize space efficiency, then productivity improves, but ensuring stability and compatibility becomes more difficult
Solution Approach 1:
The patent applies local quality by considering specific characteristics of individual packages and their local positions within the container. The scoring mechanism evaluates each package's unique properties (dimensions, weight, priority) and assigns appropriate placement based on local constraints. The solver ensures that packages with specific stability requirements are positioned in locations that maintain overall stability, while still optimizing space efficiency. This localized approach allows the system to achieve high space utilization without compromising reliability.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting scoring weights and packaging criteria based on container capacity and package characteristics. The solver modifies parameters such as priority thresholds, revenue thresholds, and packing density targets to balance space efficiency with stability requirements. By adaptively changing these parameters during the optimization process, the system can achieve optimal space utilization while maintaining package stability and compatibility.
3Productivity
If a solver is used to optimize package arrangements, then space utilization and operational efficiency improve, but the system complexity increases
Solution Approach 1:
The patent implements self-service by enabling the solver to automatically perform scoring, ranking, and arrangement of packages without requiring manual intervention. The system self-adjusts by evaluating package characteristics against predefined criteria and autonomously determines optimal configurations. This automation significantly improves operational efficiency while the modular design of the solver (with separate scoring, ranking, and packing modules) keeps system complexity manageable through structured organization.
Solution Approach 2:
The patent applies universality by designing a multi-functional solver that handles multiple tasks: scoring packages based on priority and revenue, ranking packages according to calculated scores, grouping packages into sub-lists, and determining optimal spatial arrangements. This single integrated system replaces what would otherwise require multiple separate processes and manual operations, thereby improving operational efficiency while consolidating functionality to manage overall system complexity.
4Productivity
If packages are scored and ranked based on multiple factors, then the arrangement becomes more optimized, but the computational effort increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing score values for packages based on multiple factors (priority, revenue per unit weight, revenue per unit volume) before the actual arrangement process. This pre-scoring eliminates the need to re-evaluate all packages against all criteria during the optimization process, significantly reducing computational time while maintaining high arrangement optimization. The ranked package list is generated in advance, allowing the solver to focus computational resources on spatial arrangement rather than re-evaluating package priorities.
Solution Approach 2:
The patent applies partial action by selectively evaluating and scoring only the necessary package attributes required for optimization, rather than analyzing all possible package characteristics. The scoring mechanism focuses on key factors (priority, revenue, weight, volume) that directly impact space utilization and operational efficiency, omitting less relevant details. This selective evaluation approach achieves sufficient arrangement optimization while minimizing computational effort and time requirements.
Data Source
AI summary
To determine the optimal orientation of packages within a container, packages are ranked according to a score defined by an algorithm. A first package position is determined from a first set of package dimensions and is oriented within a container. A second package position is determined from a second set of package dimensions and is oriented within the container. The packages are oriented such that the orientation of the first package position is different from the orientation of the second package position with no overlap, and a threshold portion of the lower face of the packages abuts another package or the container base. Packages are continuously oriented into the container volume until the total package volume reaches a threshold container volume, while minimizing the total package volume. The final orientation of the packages is output as a three-dimensional arrangement of the packages within the container volume.