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Worker Allocation Models with Learning and Forgetting
Transcript of Worker Allocation Models with Learning and Forgetting
Learning and Forgetting ~ Austin Chacosky Pitcher 1st Base Tom Mark 40 65 72 Compare 87 2012 Roster # Name Position Tom Mark John Ruby Andy Jason Mike Cliff Benny 3 36 57 5 71 2 4 15 8 PITCHER 1ST BASE SHORT-STOP LEFT FIELD 3RD BASE RIGHT FIELD 2ND BASE CATCHER CENTER FIELD What if we take learning rate into account? Pitcher 1st Base Tom Mark 40 + 10 every game 65 + 9 every game 72 + 4 every game 87 + 2 every game Buffer 1 Task 4 Task 2 Task 3 Task 1 Buffer 2 Buffer 3 Work for a task is drawn from the buffer of the previous task in a work flow pattern Dr. David A. Nembhard and Bryan A. Norman created a model that incorporates learning and forgetting into worker assignment decisions Workers are assigned to task on a per period basis Productivity Work Period Workers learn as they perform tasks and their productivity increases as a function of their learning and forgetting characteristics and their starting productivity. 1 1 2 2 3 3 4 5 5 4 Productivity Work Period As the number of workers increases, the solve times increases exponentially 12 1 2 3 6 9 11 10 4 5 7 8 12 1 2 3 6 9 11 10 4 5 7 8 How to approximate learning and forgetting Solve for D for each worker
for each productivity levels ijk Assign workers to productivity levels when workers have been assign to a task D times Results: Drastic reductions in solve time while maintaining solution quality
Average objective value deviation of 4.06% Impacts of Research Tip Economic
Affluence This is a huge mountain Reduce planning time from hours to minutes
Increase management flexibilty to daily workforce absenteeism
Increased total productivity of workforce Questions? Worker allocation models:
assign the workers to tasks in an ideal way
organize a workforce
incourage high worker utilization LFCM