Decision support system and method for distributed decision making for optimal human resource deployment

A method comprising:

• executing with one or more processors the steps of:
• assimilating open seat data and practitioner data;
• transforming the open seat data and practitioner data into seat attributes and practitioner attributes;
• assessing viability of matching practitioners with seats based on predetermined matching criteria, and thereupon determining feasible matches;
• determining preferred matches via integer programming and via employing the feasible matches as input;
• said determining comprising:
• maximizing a utility function which employs a weighted summation of a number of already-assigned seats, a weighted summation of compatibility scores and a weighted summation of reward/penalty scores;
• each compatibility score relating to a matching of a practitioner-seat pair, and being derived from a weighted combination of at least one matching score and at least one other criterion;
• each reward/penalty score relating to a time factor with respect to a practitioner-seat pair;
• wherein a reward is applied to at least one of:
• an overdue seat, and a practitioner remaining unassigned for a period of time;
• wherein a penalty is applied to at least one of a seat and a practitioner being scheduled for implementation in the future;
• applying a first constraint to the utility function, the first constraint ensuring that a practitioner can be assigned to one seat only;
• applying a second constraint to the utility function, the second constraint ensuring that a seat is assigned, at most, as many practitioners as the number of open positions for the seat;
• and
• delivering the preferred matches to a user interface.

A computer program product comprising:

• a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising:
• computer code configured to assimilate open seat data and practitioner data;
• computer code configured to transform the open seat data and practitioner data into seat attributes and practitioner attributes;
• computer code configured to assess viability of matching practitioners with seats based on predetermined matching criteria, and to thereupon determine feasible matches;
• computer code configured to determine preferred matches via integer programming and via employing the feasible matches as input, and further via:
• maximizing a utility function which employs a weighted summation of a number of already-assigned seats, a weighted summation of compatibility scores and a weighted summation of reward/penalty scores;
• each compatibility score relating to a matching of a practitioner-seat pair, and being derived from a weighted combination of at least one matching score and at least one other criterion;
• each reward/penalty score relating to a time factor with respect to a practitioner-seat pair;
• wherein a reward is applied to at least one of:
• an overdue seat, and a practitioner remaining unassigned for a period of time;
• wherein a penalty is applied to at least one of a seat and a practitioner being scheduled for implementation in the future;
• applying a first constraint to the utility function, the first constraint ensuring that a practitioner can be assigned to one seat only;
• applying a second constraint to the utility function, the second constraint ensuring that a seat is assigned, at most, as many practitioners as the number of open positions for the seat;
• and
• computer code configured to deliver the preferred matches to a user interface.