Method and Apparatus for Queue-Based Automated Staff Scheduling

1 . A queue-based scheduling apparatus for automated staff scheduling and for enforcing scheduling rules and requirements, comprising:

means for defining conditional and unconditional rules;

means for ranking rules and requests in varying priority as represented by a numeric value assigned to each rule and request; and

means for specifying rules both per individual and per group.

2 . The apparatus of claim 1 , further comprising:

at least one queue per each scheduled assignment for holding requests and rules.

3 . A scheduling process, comprising the steps of:

collecting requests and rules using a graphical user-interface;

determining a scheduling period that has a user-defined start date and stop date;

creating a request queue for each day of a period;

for each request or rule, determining which days said request or rule is applicable;

for each applicable day, inserting a request into its queue;

sorting said days from most constrained to least constrained;

beginning scheduling from a most constrained day;

for each assignment in a day, creating a list of candidates for that assignment for that day;

for each candidate, associating a highest priority request in said request queue that applies to said candidate, wherein said highest priority value for a candidate is a candidate bid for a chosen assignment;

sorting said candidates according to a bid calculated in the immediately preceding step;

scheduling a candidate having a highest number;

determining a schedule for any remaining days.

4 . The method of claim 3 , wherein said constraints on scheduling choices comprise either of conditional and unconditional constraints, wherein conditional constraints are only in effect if a certain scheduling condition applies.

5 . The method of claim 3 , wherein a rule applies to either of a specific individual or a group of individuals.

6 . The method of claim 3 , further comprising the step of:

associating rules with a number which describes a rank or a priority of that rule relative to other rules;

wherein a large positive number indicates that any individual under that rule is highly favored to be scheduled for the given shift on a given day;

wherein a large negative number indicates that any individual under that rule is not favored to be scheduled for the given shift on a given day; and

wherein an individual who is not subject to any rules has a priority point zero by default, indicating neutrality.

7 . The method of claim 3 , further comprising the step of:

choosing a rule having a highest absolute value of priority points for an individual to compete with other individuals when more than one rule is to be applied.

8 . The method of claim 3 , further comprising the steps of:

entering static or unconditional rules in the request queue prior to running the automated scheduler; and

entering conditional rules and requests during execution of the steps of said method, depending on the scheduling conditions;

wherein a highly adaptive scheduler is provided that changes its scheduling behavior during execution of the method, based on scheduling decisions made during execution of the method.

9 . The method of claim 3 , further comprising the step of:

providing conditional rules, wherein each conditional rule has a set of conditions and a set of actions, wherein when all conditions are met, said set of actions is converted into a request.

10 . The method of claim 3 , further comprising the step of:

providing an alternates list that exposes information in a form a user can use to override the choice that said automatic scheduler has made;

wherein said alternates list displays all constraints and requests that are currently imposed on alternate individuals.

11 . The method of claim 3 , further comprising the steps of:

said auto scheduler generating schedules in multiple phases;

wherein during each phase, said automatic scheduler entirely schedules every assignment on every day in a scheduling period;

wherein on second and later phases, said auto scheduler learns from any hazards detected in earlier phases to generate a better overall schedule;

wherein said hazards are detected whenever said automatic scheduler cannot find an individual that would not violate some rule or request;

said automatic scheduler determining if any conditional rule has forced this situation and, if it did, finding a source or a condition of the rule that generated a violating request;

said automatic scheduler generating and submitting an internal request; and

in subsequent phases, said automatic scheduler avoiding said hazard by using said submitted request from previous phases.

12 . The method of claim 3 , further comprising the steps of:

said auto scheduler randomly choosing different assignments on different days, rescheduling individuals until a global schedule improves or converges to an acceptable one; and

said auto scheduler summarizing a number of requests or rules in each queue that are in violation across all assignments in an entire schedule to determine whether a global schedule has improved after a scheduling adjustment;

wherein if a total number of violations decreases, said schedule has been improved and therefore is chosen over prior schedules.

13 . An auction method for resolving conflicting scheduling requests, comprising the steps of:

giving each scheduled individual a fixed number of points or currency to spend;

each individual then deciding how to distribute or spend said points to various requests, based on individual needs and preferences;

wherein an individual that spends the most points wins a request for an assignment for a specific day.

14 . The method of claim 13 , wherein seniority or preferential treatment is provided to individuals by giving each individual a different number of points to spend based upon said seniority or preference.

15 . The method of claim 13 , further comprising the steps of:

a scheduling administrator defining scheduling rules and policies and entering said scheduling rule and practices in the form of conditional or unconditional rules, wherein each rule is given a number that represents the priority of that rule;

users entering their request for a scheduling period, wherein said users, can assign a priority point to each of these requests, indicating a relative importance of said request;

once all rules and requests have been entered, said scheduling administrator initiating scheduling for a user-specified period defined by a begin date and an end date;

sorting said rules and requests for a given assignment for a day based on the value of said priorities;

matching candidates with requests to arrive at a candidate with a highest request priority, which is a scheduling choice for an assignment for that day;

once a schedule has been generated, said scheduling administrator optionally inspecting each scheduling choice and reviewing alternates for any particular assignment; and

when said schedule is complete, making said schedule available.

16 . An automated staff scheduling method, comprising the steps of:

allowing a large number of conflicting requests and rules to be entered;

said requests and rules competing in a scheduling decision based on numerical priority associated with said requests and rules.

17 . The method of claim 16 , further comprising the step of:

resolving conflicts that arise in said scheduling decision.

18 . The method of claim 16 , further comprising the step of:

implementing rules and exceptions to rules.

19 . The method of claim 16 , further comprising the step of:

implementing auction-based bidding for contentious assignments and days based on which request has the highest priority.

20 . The method of claim 16 , further comprising the step of:

exposing a rationale for a scheduling decision to a user by showing who is scheduled, their constraints, and a cause for said constraints.

21 . The method of claim 16 , further comprising the step of:

manipulating a local queue of requests for each assignment.