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Line Balancing Algorithm for Multi-Manned Stations


I need someone to create an algorithm for me that balances the workload in an assembly line.

The algorithm is supposed to assign tasks to workstations and thereby consider the station’s capacity (given as takt time in seconds).

The target is to minimize the number of required stations by optimally arranging the tasks under consideration of precedence constraints and the tasks’ respective execution times.

While this is a simple assembly line balancing problem, my problem is a bit advanced:

The algorithm needs to be able to consider that each station can have 2 workers instead of only 1 and the work between those 2 workers within one station needs to be scheduled as well.

Both workers have different execution times for same tasks.

Due to the task precedences, it can happen, that within a station, worker 1 needs to wait until worker 2 has his task completed to be able to continue his own tasks. So the throughput time of a station is not just the sum of execution times of tasks allocated to this station but needs to be extended by the wait times that workers face when waiting for the other worker at the same station.

This represents an “assembly line balancing problem with multi-manned stations”

Input data is the following and should be read from an Excel file:

- Task list

- Task precedence diagram

- Task assignment (worker 1 or worker 2 or both)

- Execution times for each task for worker 1 or 2

- Takt time

Output that would be minimally required and written into an Excel file:

- Number of required stations

- Tasks assigned to stations

- Utilization of stations (% of takt)

I’m flexible with the optimization method used (enumeration, genetic, branch&bound, …) and the implementation environment (R, python, Visual Studio/C#, …)


Квалификация: Алгоритмы, Программирование на С, Operations Research, Python

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ID проекта: #19700652



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