int new_start(int *intour, heur_prob *p, int start, int num_cust)
{
int starter = 0, start_pos, cust, count=0;
int cost = -MAXINT, temp_cost;
int vertnum = p->vertnum;
if (start == FAR_INS)
for (cust=1; cust<vertnum; cust++) {
if (((temp_cost = ICOST(&p->dist, 0, cust)) > cost) &&
(intour[cust] != IN_TOUR)) {
starter = cust;
cost = temp_cost;
}
}
else {
start_pos = rand()%num_cust+1;
for (cust = 1, count = 0; count<start_pos; cust ++)
if (intour[cust] != IN_TOUR) count ++;
starter = cust-1;
}
return(starter);
}
void make_routes(heur_prob *p, _node *tsp_tour, int start,
best_tours *new_tour)
{
int cur_node, prev_node, route_beg, prev_route_beg;
int weight, i, capacity = p->capacity;
int cur_route = 1;
int cost;
_node *tour = new_tour->tour;
adj_list **adj;
adj_list *temp, *path;
int *pi, route_end;
int vertnum = p->vertnum;
int *demand = p->demand;
adj = (adj_list **) calloc (vertnum, sizeof(adj_list *));
/*--------------------------------------------------------------------*\
| First we must construct the graph to give to the shortest path |
| algorithm. In this graph, the edge costs are as follows. The cost of |
| edge between nodes i and j is the cost of a route beginning with i's |
| successor on the TSP tour and ending with j (in bewtween, the route |
| follows the same ordering as the TSP tour itself) if this is a |
| feasible route and infinity otherwise. Now if we find a |
| shortest cycle in this graph, then the nodes in the cycle will be the|
| endpoints of the routes in an optimal partition. This is what I do. |
| We need to arbitrarily specify the fist endpoint in advance. |
| This is the value contained the start variable. The tsp_tour |
| structure contains the original TSP tour. |
\*--------------------------------------------------------------------*/
for (prev_route_beg = start, route_beg = tsp_tour[start].next, i=0;
i<vertnum-1; prev_route_beg = route_beg,
route_beg = tsp_tour[route_beg].next, i++){
cur_node = route_beg;
prev_node = 0;
temp = adj[prev_route_beg] = (adj_list *) calloc (1, sizeof(adj_list));
weight = demand[cur_node];
cost = ICOST(&p->dist, prev_node, cur_node);
temp->cost = cost + ICOST(&p->dist, 0, cur_node);
temp->custnum = cur_node;
prev_node = cur_node;
cur_node = tsp_tour[cur_node].next;
while (weight + demand[cur_node] <= capacity){
weight += demand[cur_node];
cost += ICOST(&p->dist, prev_node, cur_node);
temp->next = (adj_list *) calloc (1, sizeof(adj_list));
temp = temp->next;
temp->cost = cost + ICOST(&p->dist, 0, cur_node);
temp->custnum = cur_node;
prev_node = cur_node;
cur_node = tsp_tour[cur_node].next;
}
}
/* The graph is constructed. Now find a shortest cycle in it */
pi = sp(adj, vertnum, start, start);
/*--------------------------------------------------------------------*\
| Now the shortest cycle information is contained in pi. However, using|
| pi, we can only trace the shortest cycle in one direction since it is|
| actually stored as a directed path from the start node to itself. |
| Also, we can only trace the TSp tour in one direction since it is |
| stored in the same way. So we must store the cycle in the reverse |
| direction in order to break up the TSP tour. That is what this piece |
| of code does. It stores the nodes on the cycle in opposite order in a|
| linked list to be used in the next part of the code. |
\*--------------------------------------------------------------------*/
path = (adj_list *) calloc (1, sizeof(adj_list));
path->custnum = start;
cur_node = pi[start];
while (cur_node){
temp = (adj_list *) calloc (1, sizeof(adj_list));
temp->custnum = cur_node;
temp->next = path;
path = temp;
cur_node = pi[cur_node];
}
temp = path;
/*--------------------------------------------------------------------*\
| Now we have the optimal break points stored in order in a liked list.|
| We trace the TSP tour, copying each node into the VRP tour until we |
| reach the endpoint of a route and then we change the route number. |
\*--------------------------------------------------------------------*/
tour[0].next = tsp_tour[start].next;
cur_node = tour[0].next;
route_end = temp->custnum;
for (i=1; i<vertnum-1; i++){
tour[cur_node].next = tsp_tour[cur_node].next;
tour[cur_node].route = cur_route;
if (cur_node == route_end){
cur_route++;
if (temp->next){
temp = temp->next;
route_end = temp->custnum;
}
else break;
}
cur_node = tsp_tour[cur_node].next;
}
tour[cur_node].next = 0;
tour[cur_node].route = cur_route;
new_tour->cost = compute_tour_cost(&p->dist, tour);
new_tour->numroutes = cur_route;
}
void nearest_ins(int parent, heur_prob *p)
{
printf("\nIn nearest_ins....\n\n");
int numroutes, cur_route, nearnode, *starter;
int mytid, info, r_bufid;
int *intour;
int last, cost;
neighbor *nbtree;
_node *tour;
route_data *route_info;
int start;
best_tours *tours;
double t=0;
mytid = pvm_mytid();
(void) used_time(&t);
tours = p->cur_tour = (best_tours *) calloc (1, sizeof(best_tours));
/*-----------------------------------------------------------------------*\
| Receive the VRP data |
\*-----------------------------------------------------------------------*/
PVM_FUNC(r_bufid, pvm_recv(-1, ROUTE_NINS_VRP_DATA));
PVM_FUNC(info, pvm_upkbyte((char *)tours, sizeof(best_tours), 1));
tour = p->cur_tour->tour = (_node *) calloc (p->vertnum, sizeof(_node));
PVM_FUNC(info, pvm_upkbyte((char *)tour, (p->vertnum)*sizeof(_node), 1));
numroutes = p->cur_tour->numroutes;
starter = (int *) calloc (numroutes, sizeof(int));
route_info = p->cur_tour->route_info
= (route_data *) calloc (numroutes+1, sizeof(route_data));
PVM_FUNC(r_bufid, pvm_recv(-1, ROUTE_NINS_START_RULE));
PVM_FUNC(info, pvm_upkint(&start, 1, 1));/*receive the start
rule*/
if (start != FAR_INS) srand(start); /*if the start rule is random, then*\
\*initialize the random number gen.*/
starters(p, starter, route_info, start);/*generate the route starters for*\
\*all the clusters. */
/*-----------------------------------------------------------------------*\
| Allocate arrays |
\*-----------------------------------------------------------------------*/
nbtree = (neighbor *) malloc (p->vertnum * sizeof(neighbor));
intour = (int *) calloc (p->vertnum, sizeof(int));
/*-----------------------------------------------------------------------*\
| Find the nearest insertion tour from 'starters' |
\*-----------------------------------------------------------------------*/
for (cur_route=1; cur_route<=numroutes; cur_route++){
/*---------------------------------------------------------------------*\
| The first part of this loop adds the starter and the nearest node to |
| it into the route to initialize it. Then a function is called |
| which inserts the rest of the nodes into the route in nearest |
| insert order. |
\*---------------------------------------------------------------------*/
if (route_info[cur_route].numcust <= 1) continue;
cost = 0;
last = 0;
intour[0] = 0;
intour[starter[cur_route-1]] = IN_TOUR;
ni_insert_edges(p, starter[cur_route-1], nbtree, intour, &last, tour, cur_route);
nearnode = closest(nbtree, intour, &last);
intour[nearnode] = IN_TOUR;
ni_insert_edges(p, nearnode, nbtree, intour, &last, tour, cur_route);
tour[starter[cur_route-1]].next = nearnode;
tour[nearnode].next = starter[cur_route-1];
if (starter[cur_route - 1] == 0)
route_info[cur_route].first = route_info[cur_route].last = nearnode;
if (nearnode == 0)
route_info[cur_route].first = route_info[cur_route].last
= starter[cur_route-1];
cost = 2 * ICOST(&p->dist, starter[cur_route-1], nearnode);
cost = nearest_ins_from_to(p, tour, cost, 2, route_info[cur_route].numcust+1,
starter[cur_route-1],
nbtree, intour, &last, route_info, cur_route);
route_info[cur_route].cost = cost;
}
tour[0].next = route_info[1].first;
/*-------------------------------------------------------------------------*\
| This loop points the last node of each route to the first node of the next|
| route. At the end of this procedure, the last node of each route is |
| pointing at the depot, which is not what we want. |
\*-------------------------------------------------------------------------*/
for (cur_route = 1; cur_route< numroutes; cur_route++)
tour[route_info[cur_route].last].next = route_info[cur_route+1].first;
cost = compute_tour_cost(&p->dist, tour);
/*-----------------------------------------------------------------------*\
| Transmit the tour back to the parent |
\*-----------------------------------------------------------------------*/
send_tour(tour, cost, numroutes, tours->algorithm, used_time(&t), parent,
p->vertnum, 1, route_info);
if ( nbtree ) free ((char *) nbtree);
if ( intour ) free ((char *) intour);
if ( starter) free ((char *) starter);
free_heur_prob(p);
}
void tsp_fini(int parent, heur_prob *p)
{
printf("\nIn tsp_fini....\n\n");
int mytid, info, r_bufid;
int starter, farnode, v0, v1, cur_start;
_node *tsp_tour, *tour, *opt_tour;
int maxdist;
int *intour;
int last, cost;
int i, j;
neighbor *nbtree;
int trials, interval;
int farside, vertnum;
best_tours *opt_tours, *tours;
double t=0;
mytid = pvm_mytid();
(void) used_time(&t);
/*-----------------------------------------------------------------------*\
| Receive the VRP data |
\*-----------------------------------------------------------------------*/
PVM_FUNC(r_bufid, pvm_recv(-1, TSP_FINI_TRIALS));
PVM_FUNC(info, pvm_upkint(&trials, 1, 1));
PVM_FUNC(r_bufid, pvm_recv(parent, TSP_FINI_RATIO));
PVM_FUNC(info, pvm_upkint(&farside, 1, 1));
/*-----------------------------------------------------------------------*\
| Receive the starting point |
\*-----------------------------------------------------------------------*/
PVM_FUNC(r_bufid, pvm_recv(-1, TSP_START_POINT));
PVM_FUNC(info, pvm_upkint(&starter, 1, 1));
vertnum = p->vertnum;
if (starter == vertnum)
for (starter=v0=1, maxdist=ICOST(&p->dist, 0,1); v0<vertnum-1; v0++)
for (v1=v0+1; v1<vertnum; v1++)
if (maxdist < ICOST(&p->dist, v0, v1)){
maxdist = ICOST(&p->dist, v0, v1);
starter = v0;
}
/*-----------------------------------------------------------------------*\
| Allocate arrays |
\*-----------------------------------------------------------------------*/
tsp_tour = (_node *) malloc (vertnum * sizeof(_node));
nbtree = (neighbor *) malloc (vertnum * sizeof(neighbor));
intour = (int *) calloc (vertnum, sizeof(int));
tours = p->cur_tour = (best_tours *) calloc (1, sizeof(best_tours));
tour = p->cur_tour->tour = (_node *) calloc (vertnum, sizeof(_node));
opt_tours = (best_tours *) malloc (sizeof(best_tours));
opt_tour = (_node *) malloc (vertnum*sizeof(_node));
/*------------------------------------------------------------------------*\
| This heuristic is a so-called route-first, cluster-second heuristic. |
| We first construct a TSP route by farnear insert and then partition it |
| into feasible routes by finding a shortest cycle of a graph with edge |
| costs bewtween nodes being defined to be the cost of a route from one |
| endpoint of the edge to the other. |
\*------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------*\
| Find the first 'farside node with farthest insertion from 'starter' |
\*-----------------------------------------------------------------------*/
last = 0;
intour[0] = IN_TOUR;
intour[starter] = IN_TOUR;
tsp_fi_insert_edges(p, starter, nbtree, intour, &last);
farnode = tsp_farthest(nbtree, intour, &last);
intour[farnode] = IN_TOUR;
tsp_fi_insert_edges(p, farnode, nbtree, intour, &last);
tsp_tour[starter].next = farnode;
tsp_tour[farnode].next = starter;
cost = 2 * ICOST(&p->dist, starter, farnode);
farside = MAX(farside, 2);
cost = tsp_farthest_ins_from_to(p, tsp_tour, cost,
2, farside, starter, nbtree, intour, &last);
/*------------------------------------------------------------------------*\
| Order the elements in nbtree (and fix the intour values) so after that |
| nbtree is suitable to continue with nearest insertion. |
\*------------------------------------------------------------------------*/
qsort((char *)(nbtree+1), last, sizeof(neighbor), compar);
for (i=1; i<=last; i++)
intour[nbtree[i].nbor] = i;
/*-----------------------------------------------------------------------*\
| Continue with nearest insertion |
\*-----------------------------------------------------------------------*/
cost = tsp_nearest_ins_from_to(p, tsp_tour, cost,
farside, vertnum-1, starter, nbtree, intour,
&last);
/*------------------------------------------------------------------------*\
| We must arbitrarily choose a node to be the first node on the first |
| route in order to start the partitioning algorithm. The trials variable |
| tells us how many starting points to try. Its value is contained in |
| p->par.tsp.numstarts. |
\*------------------------------------------------------------------------*/
if (trials > vertnum-1) trials = vertnum-1;
interval = (vertnum-1)/trials;
opt_tours->cost = MAXINT;
/*------------------------------------------------------------------------*\
| Try various partitionings and take the solution that has the least cost |
\*------------------------------------------------------------------------*/
for (i=0, cur_start = starter; i<trials; i++){
make_routes(p, tsp_tour, cur_start, tours);
if (tours->cost < opt_tours->cost){
(void) memcpy ((char *)opt_tours, (char *)tours, sizeof(best_tours));
(void) memcpy ((char *)opt_tour, (char *)tour, vertnum*sizeof(_node));
}
for (j=0; j<interval; j++)
cur_start = tsp_tour[cur_start].next;
}
/*-----------------------------------------------------------------------*\
| Transmit the tour back to the parent |
\*-----------------------------------------------------------------------*/
send_tour(opt_tour, opt_tours->cost, opt_tours->numroutes, TSP_FINI,
used_time(&t), parent, vertnum, 0, NULL);
if ( nbtree ) free ((char *) nbtree);
if ( intour ) free ((char *) intour);
if ( opt_tours ) free ((char *) opt_tours);
if ( opt_tour ) free ((char *) opt_tour);
if ( tsp_tour ) free ((char *) tsp_tour);
free_heur_prob(p);
}
