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Workforce Optimization Modules

Capable of handling various practical constraints, such as employee requests, time-of-day requirements, task-specific requirements, and skill-based requirements.

Large-scale problems can also be solved efficiently.

The Need for Workforce Optimization

It is becoming increasingly difficult to secure necessary personnel due to the declining workforce, and shift management is becoming more complex due to the diversification of working styles such as full-time, part-time, and flextime.

In addition, creating staffing plans that incorporate various requests from the workers' side due to the diversification of people's lifestyles can improve employee satisfaction and labor productivity.

Applicable Problems

1．Daily Shift Optimization

This is a plan to maximize work efficiency while considering the work-life balance of employees. It is possible to create a monthly work schedule for dozens or hundreds of people by dividing the day into 3-4 shifts, and to create plans that accurately consider work and breaks in finer time units such as 15 minutes or 30 minutes.

Examples: Applicable to industries such as retail, food service, healthcare, and manufacturing.

2．Multi-Location Workforce Optimization

For companies operating in multiple locations, it allocates the best location for each employee's work, considering the needs of each location and the skills of the employees.

Examples: Applicable to logistics, healthcare, retail, and other industries.

3．Workforce Optimization Considering Travel

This is a plan to efficiently allocate employees when they need to move to different locations as part of their work. It requires planning that considers not only staffing but also efficient movement.

Examples: This includes staffing for maintenance and inspection that requires visiting multiple locations, and staffing for nursing care and home medical care.

4．Workforce Optimization Considering Resources

This is a plan to allocate personnel considering the resources (rooms, equipment, devices, etc.) required for each task and the timing when those resources are available.

Examples: This includes surgery schedules in hospitals (doctors and nurses and rooms), corporate training schedules (instructors and rooms), university faculty and classroom assignments, and staffing in factories.

5．Crew Rostering Optimization

This is a plan to optimize the work schedules of crew members (drivers, operators, and attendants) in the transportation industry, such as airlines, railways, ships, and buses. It requires consideration of various constraints such as working hour restrictions, operating schedules, skill levels, and accommodation, and large-scale problems can become optimization problems involving thousands of people. However, appropriate planning is possible using MOAI solutions.

Optimization Algorithm Performance

Regarding optimization algorithms, we conduct experimental analysis on as many benchmark problem instances as possible, and have confirmed that they perform as well as or better than state-of-the-art (SOTA) algorithms. In addition, we have achieved speed improvements of several to hundreds of times compared to SOTA algorithms by using our unique technologies such as the fusion of machine learning and optimization algorithms (MOAI) and automatic selection from multiple optimization algorithms.

How to Implement

  1. A Proof of Concept (PoC) using the MOAI platform is possible before implementation, allowing for quick validation of effectiveness.
  2. Customization is only performed when necessary.
  3. The service is provided as a cloud service (SaaS), but API provision and on-premise usage are also supported. Please contact us for details.
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