Design of an Automatic Control Algorithm for Energy-Efficient ...

Optimiser code 155
52 return 10;
54 ordPrio = (int_T∗) malloc (( Obj .numObj+1)∗Obj .numObj∗ sizeof(int_T) ) ;
if(ordPrio == NULL)
56 return 10;
58 fitness = (real_T∗) malloc (Opt. popSize∗sizeof(real_T) ) ;
if(fitness == NULL)
60 return 10;
62 parents = (int_T∗) malloc (2∗Opt . numChild∗ sizeof(int_T) ) ;
if(parents == NULL)
64 return 10;
66 /∗ initialise RNG ∗/
68
/∗PlantSeeds(time(NULL)) ; needs to be done once outside this function∗/
/∗ C a l c u l a t e maximum canges based on t h e change of the fitness (hypermutation) ∗/
70 if(ExVal . f i t [ 0 ] == ERROR_FITNESS) /∗ Start or limit exceeded ∗/
max_change = Opt . adapMutFractionMax ;
72 else if (( ExVal . f i t [0] Opt . adapMutFractionMin ) /∗ always allow minimal change
∗/
74 max_change = ExVal . explFactor [0] Opt. adapMutFractIncr ;
else if (( ExVal . f i t [0] >ExVal . f i t _last [0])
76 && ExVal . explFactor [ 0 ] < Opt . adapMutFractionMax) /∗ Never allow more than
78 else
maximum ∗/
max_change = ExVal . explFactor [0]+Opt . adapMutFractIncr ;
max_change = ExVal . explFactor [ 0 ] ;
80 #if DEBUG_IMEA >= 2
82 #endif
84
printf("==last= %f ===old= %f===\n" , ExVal . f i t [ 0 ] , ExVal . f i t _last [0]) ;
/∗ Initialise population ∗/
/∗ create initial population ∗/
86 IMEA_initPop(pop , Opt. basePop , ExVal . elitePop , Opt. popSize , Opt. numElite , Opt.numBase
, DV. numDV,DV. l b , DV. ub ) ;
/∗ Evaluate the fitness of the initial population ∗/
88 IMEA_evaluateObjectives(pop , Sys , Obj. objectiveFctArray , Estim_SYS_States , Opt.
90
s i m H o r i z o n , Opt . simSampleT , Opt . p o p S i z e , DV. numDV, Obj . numObj ) ;
IMEA_priorisedWeighting(pop , Obj , ordPrio , Opt. popSize , DV.numDV) ;
/∗ Main loop ∗/
92 for( i =0; i