A python based matter allocation problem with the following parameters
Client: The number of clients considered in the problem
FE: This is the total number of fee-earners that are able to work on the considered type of matters irrespective of who the client is
FE_Per_Client: The minimum and maximum number of fee-earners that are expected to have a relationship with any give client
Capacity_Per_FE: This is the minimum and maximum number of matters a fee-earner can work on simultaneously.
Lifecycle: This is the minimum and maximum expected lifecycle of any given matter
Jobs_Per_Client: This is the minimum and maximum number of matters expected to be received from a client per day
Utilisation: This is the minimum and maximum number of matters a fee-earner is working on before new jobs are assigned
Set these parameters in Problem/Problem_Definition.py
Set the path to the problem ('./Data' in this case) in Problem/Generate_Problems.py
Run Problem/Generate_Problems.py to generate new problems.
Each problem contains 4 files:
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Client_FE_Lifecyle.txt: contains the lifecycle of each fee-earner per client
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Day_Job_Client.txt: contains the earliest start day, matter id and client id (we use a 28-day period in this study)
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FE_Capacity.txt: contains the capacity of each fee-eaner
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FE_Schedule.txt: contains previously allocated matters and the finish times