with Tasks; use Tasks;
with Task_Set; use Task_Set;
with paes; use paes;
with Scheduler;             use Scheduler;
with Scheduler_Interface;   use Scheduler_Interface;
with Ada.Strings.Unbounded;             use Ada.Strings.Unbounded;
with unbounded_strings;                 use unbounded_strings;
with framework_config; use framework_config;
 
package Task_Clustering_Rules is
 
  
  Initial_tasks_set : Tasks_Set;
  Hyperperiod_of_Initial_Taskset : integer;
  The_Scheduler : Schedulers_Type;
  Task_priority : Integer;
  Sched_policy  : Policies;
  Second_fitness_function : unbounded_String; 

  --------------------------------------------------------------------------
  -- Declaration of the **Anti-Ideal point** (which represent the "worst"
  -- value of each objective, explored in the search space) In our case 
  -- we deal with a minimization problem, so "worst" means the maximum value
  -- can be taken by each objective.
  -- these values shoult be determined among all iterations
  ---------------------------------------------------------------------------
  Z1_anti_ideal, Z2_anti_ideal: Float;

  ---------------------------------------------------------------------------
  -- and the **Ideal point** which is defined by 
  -- the "better" value of each objective, 
  -- explored in the search space (i.e. the min value of each objective)
  -- These values are determined from the final archive
  ---------------------------------------------------------------------------
  Z1_ideal, Z2_ideal : Float;
 
  -- Generate a schedulable task set 
  -- using the UUnifast method to generate utilizations of tasks 
  -- from a total utilization.
  procedure Generate_initial_schedulable_task_set
     (my_tasks         : in out Tasks_Set;
      N                : in Integer;
      U 	       : in Float);

  -- Return the number of tasks from a given solution
  function Number_of_tasks (s : in solution) return integer;

  -- Applying clustering rules on a given solution 
  -- and return the resulting task set
  function Appling_clustering_rules (s : in solution) return Tasks_Set;

  -- Build an xml file from a task set
  procedure Build_xml_model (my_tasks  : in Tasks_Set; file_name : string);

  -- this function verify if a solution is consistent or not i.e verify if
  -- there are two non-harmonic functions which are grouped alone in the same task.
  function Is_sol_consistent (s : in solution) return boolean;
  
end Task_Clustering_Rules;