The Doctor Rostering Problem - Asser Fahrenholz

2
Appendix A. Implementation 62
3 import basic . RCLParameter ;
4 import heuristic . Heuristic ;
5
6 import java . util . Vector ;
7
8 import basic . Rules ;
9 import changes . Change ;
10 import ds.Day ;
11 import ds. Doctor ;
12 import ds. Pair ;
13 import ds. Schedule ;
14 import ds. Shift ;
15 import java . util . HashMap ;
16 import java . util . HashSet ;
17
18 /* *
19 * The extended version of the greedy approach to assigning the shifts is based
20 * on a relative behaviour . It examines each doctor for each shift and picks the
21 * best doctor . This doctor is based on a score , which again is based on the
22 * rules documented in the report , as well as in Rules
23 *
24 * @author Asser Fahrenholz
25 */
26 public class GreedyExt extends Heuristic {
27
28 public Vector < Shift > unassignedShifts ;
29 private final RCLParameter RCLsize ;
30 private int newScore ;
31 private int oldScore ;
32 private int newVio ;
33 private int newSoftVio ;
34 private boolean minimize ;
35
36 public GreedyExt ( Rules myRules , RCLParameter RCLsize , Schedule s, DayOrShift
dos , boolean minimize ) {
37 super ( myRules , s, RCLsize , dos );
38 this . minimize = minimize ;
39 this . RCLsize = RCLsize ;
40 }
41
42 public RCLParameter getRCL () {
43 return this . RCLsize ;
44 }
45
46 @Override
47 public Void doInBackground () throws Exception {
48 try {
49 Pair < Integer , Pair < HashMap < Shift , HashSet >>,
HashMap < Shift , HashSet >>>> workingSol = working .
getSolutionValue ( false , getRules ());
50 oldScore = 0;
51
52 newScore = workingSol . getE ();
53 newVio = workingSol . getV (). getE (). size ();