Trailer Pallet Unstacking Optimization for Feasible Load Plans
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Solution Overview
Problem
Unplanned pallets resulting from inefficient manual handling of loading plans for trailers create complex and time-consuming issues in logistics operations.
Innovation Solution
An automated unstacking optimization system that modifies load plans by unstacking and redistributing pallets to optimize trailer space, reducing unplanned pallets and empty floor spots through iterative algorithms and feasibility checks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual means are used to address unplanned pallets, then flexibility in handling loading plans is maintained, but the process becomes complex and inefficient
Solution Approach 1:
The patent replaces manual mechanical handling of loading plans with an automated computer-based system that uses algorithms to generate and optimize loading plans, directly addressing unplanned pallets without human intervention
Solution Approach 2:
The system enables self-service by automatically detecting unplanned pallets and generating corrected loading plans without requiring manual analysis or adjustment by operators
2Productivity
If automated optimization is implemented, then productivity and efficiency are improved, but device complexity increases
Solution Approach 1:
The system performs multiple functions including generating loading plans, identifying unplanned pallets, optimizing stack configurations, and validating against constraints within a single integrated platform, reducing the need for separate complex systems
Solution Approach 2:
The optimization process is divided into discrete algorithmic steps including initial plan generation, unplanned pallet identification, unstacking optimization, and validation, making the complex system manageable and modular
3Area of stationary object
If more pallets are loaded to reduce empty floor spots, then space utilization improves, but loading constraints and feasibility rules may be violated
Solution Approach 1:
The system dynamically adjusts loading plans by iteratively modifying stack configurations and pallet positions while continuously validating against constraints, allowing flexible adaptation to maximize space without violating rules
Solution Approach 2:
The system incorporates feedback loops where each proposed loading configuration is validated against feasibility rules and constraints, with automatic correction of violations through iterative optimization
4Reliability
If stacks are unstacked and redistributed to reduce unplanned pallets, then loading plan feasibility improves, but additional processing time is required
Solution Approach 1:
The system performs preliminary identification of unplanned pallets and potential unstacking opportunities before finalizing the loading plan, allowing proactive resolution of feasibility issues rather than reactive corrections
Solution Approach 2:
The system efficiently evaluates multiple parameter changes in stack configurations and pallet positions using optimized algorithms, reducing the computational time required to explore alternative loading arrangements
Data Source
AI summary
A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions, that when executed on the one or more processors, cause the one or more processors, to perform: obtaining a first load plan, wherein the first load plan comprises a set of stacks assigned to floor spots of a trailer; determining that at least one of (a) there is an empty floor spot in the first load plan for the trailer or (b) the first load plan is infeasible; determining a target number of stacks for an updated load plan; iterating, via simulated annealing, through modifications to the updated load plan; terminating the iterating when a predetermined termination criteria is satisfied; and outputting the updated load plan. Other embodiments are disclosed.