PopulationMap<Point,Class>
IteratedLocalSearch(const PopulationMap<Point,Class>& map,
int iterations) {
const int local_search_its = 100;
PopulationMap<Point,Class> initial_solution(map);
PopulationMap<Point,Class> best_solution = LocalSearchFirstFound(initial_solution, local_search_its);
float curr_quality = best_solution.EvaluateQuality();
repeat (iterations) {
PopulationMap<Point,Class> perturbated_solution(best_solution);
perturbated_solution.reset();
// TODO: add diversification if the solution is not improving a lot (define 'a lot')
perturbated_solution.NeighborhoodOperator(false);
const PopulationMap<Point,Class>& candidate_solution = LocalSearchFirstFound<Point, Class>(perturbated_solution, local_search_its);
float candidate_quality = candidate_solution.EvaluateQuality();
// If the quality is better than the previous map, we found a new map
if (candidate_quality > curr_quality) {
best_solution = candidate_solution;
curr_quality = candidate_quality;
}
}
return best_solution;
}
Graph* tabu_search(Graph* graph, int tabu_len, int candidates_len, int max_iter,
int* colors){
Graph* best = initial_solution(graph);
int best_cost = cost(best);
int new_best_cost = best_cost - 1;
Graph* s = reduce_color(best, new_best_cost);
int conflict_c;
char** conflict_vt = conflict_vertices(s, &conflict_c);
int tabu_pos = 0;
tabu_t** tabu_list = (tabu_t**) malloc(sizeof(tabu_t*) * candidates_len
* graph->iterator_size);
int iter = 0;
while (iter < max_iter){
Graph** candidates = (Graph**) malloc(sizeof(Graph*) * candidates_len);
if (conflict_c > 0){
for (int i = 0; i < candidates_len; i++){
candidates[i] = generate_candidates(s, conflict_vt, conflict_c,
tabu_list, &tabu_pos, new_best_cost);
}
int conflict_cand_c;
Graph* best_candidate = get_best_candidate(candidates, candidates_len,
conflict_vt, conflict_c, &conflict_cand_c);
if (conflict_c > conflict_cand_c){
free_graph(s);
free(conflict_vt);
s = best_candidate;
conflict_vt = conflict_vertices(s, &conflict_c);
}
else if (best_candidate != NULL)
free_graph(best_candidate);
}
if (conflict_c == 0){
best_cost = new_best_cost;
free_graph(best);
best = s;
new_best_cost = best_cost - 1;
s = reduce_color(best, new_best_cost);
free(conflict_vt);
conflict_vt = conflict_vertices(s, &conflict_c);
}
if (tabu_pos > tabu_len)
update_tabu_list(tabu_list, &tabu_pos, tabu_len);
free(candidates);
iter++;
}
free(conflict_vt);
free(tabu_list);
if (colors != NULL)
*colors = best_cost;
return best;
}
