Automated Rotation Tool for Crew Scheduling Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Large enterprises face complexity in scheduling workers across wide geographic areas, particularly in non-stationary locations like cruise ships, due to the need for efficient placement of crew members with specific skills and constraints such as travel costs and gender/nationality balance, which current manual and database-based methods fail to optimize effectively.
Innovation Solution
An automated rotation tool that uses a scheduling database to generate postings for vacant positions based on rules and parameters, including travel optimization and balance requirements, and integrates with travel booking systems to minimize vacancy times and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual scheduling methods are used, then ease of operation is maintained, but productivity and scheduling optimization deteriorate
Solution Approach 1:
The scheduling system performs self-optimization by automatically analyzing vacancy data, personnel rosters, and travel information to generate optimal schedules without requiring manual intervention. The system self-adjusts to accommodate constraints such as travel costs, gender balance, and skill requirements, thereby achieving high productivity while maintaining operational simplicity through automation.
Solution Approach 2:
The patent replaces manual mechanical scheduling processes with an automated computer-based system that uses algorithms to optimize crew assignments. This substitution eliminates the need for manual calculation and adjustment, significantly improving scheduling efficiency and optimization while reducing the operational burden on human schedulers.
2Productivity
If automated scheduling algorithms are implemented, then scheduling optimization and productivity improve, but ease of operation and system complexity management worsen
Solution Approach 1:
The system incorporates feedback mechanisms that continuously monitor scheduling outcomes and adjust algorithms accordingly. By analyzing actual performance data against predetermined constraints and objectives, the system refines its optimization processes, maintaining high productivity while adapting to changing operational requirements and keeping the system manageable through iterative improvement.
Solution Approach 2:
The patent utilizes parameter changes by allowing administrators to modify scheduling constraints, weights, and optimization criteria through user-friendly interfaces. The system dynamically adjusts its behavior based on changing parameters such as travel cost thresholds, gender balance requirements, or skill level preferences, enabling flexible optimization while keeping the complexity hidden from end users through automated parameter processing.
3Manufacturing precision
If comprehensive scheduling constraints are applied, then scheduling precision and compliance improve, but device complexity and processing requirements worsen
Solution Approach 1:
The scheduling algorithm is segmented into modular constraint handling components, each responsible for specific requirements such as travel cost limits, gender balance, nationality distribution, or skill matching. This segmentation allows the complex scheduling problem to be broken down into manageable sub-problems, improving schedule accuracy through comprehensive constraint application while reducing overall algorithm complexity through structured modular design.
Solution Approach 2:
The system performs preliminary actions by pre-processing and validating scheduling constraints, travel itineraries, and personnel qualifications before generating final schedules. This preliminary validation ensures that all constraints are properly understood and accounted for, improving schedule accuracy while reducing the computational complexity of the main scheduling algorithm by eliminating invalid or conflicting constraints in advance.
Data Source
AI summary
Various embodiments provide a scheduling system structured for generating at least one posting to fill a vacant post on a schedule. In an embodiment, the scheduling system includes a scheduling database and an automated rotation tool. The scheduling database includes a personnel roster and a schedule. The schedule includes a vacant post. The scheduling database transmits the schedule and the personnel roster to the automated rotation tool. The automated rotation tool includes a computer system, and receives the personnel roster and the vacant post beginning within the vacancy window from the scheduling database, and also receives a rule, a parameter, and a vacancy window. The automated rotation tool generates a posting assigning a person from the personnel roster to the vacant post according to the rule and the parameter, and transmits the posting to the scheduling database.