System, method and product for rostering using dynamic gene...

Details System, method and product for rostering using dynamic gene... System, method and product for rostering using dynamic gene...

2007-04-17

2009-10-20

Vincent, David R (Department: 2129)

Data processing: artificial intelligence

Machine learning

Genetic algorithm and genetic programming system

Reexamination Certificate

active

07606773

ABSTRACT:
A genetic algorithms rostering system (20) with a workload and shift setting optimizer (22), a GA rostering engine (24) and a storage medium (26) is described. The GA rostering engine (24) dynamically shifts one or more shift lists of an initial shift list matrix based upon a shifting factor associated with each of the shift lists. Thereafter, the GA rostering engine (24) obtains an intermediate shift list matrix that is then fine-tuned by swapping individual shifts for each of the shift lists in the intermediate shift list matrix. A swapping factor for fine-tuning is associated with each of the shift lists and indicates a gene group with two or more genes. Each of the genes in the gene group is associated with an individual shift. Output of the rostering system (20) are rosters (28) represented in a matrix form.

REFERENCES:
Boyd JC, Savory J. “Genetic algorithm for scheduling of laboratory personnel”. Clin Chem. Jan. 2001;47:118-123.
Edmund Burke , Peter Cowling , Patrick De Causmaecker , Greet Vanden Berghe,“ A Memetic Approach to the Nurse Rostering Problem”, Applied Intelligence, v.15 n.3, p. 199-214, Nov.-Dec. 2001.
Aickelin U, Dowsland K (2000). “Exploiting problem structure in a genetic algorithm approach to a nurse rostering problem.” Journal of Scheduling 3, 139-153.
Tanomaru J. “Staff Scheduling by a Genetic Algorithm with Heuristic Operators”. Proceedings of the IEEE. Reference on Evolutionary Computation 1995; 456-461.

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