last[seq] + SERVE_TIME + tm[seq, (0,)],
0, 0, (ds[(0,), seq] + ds[seq, (0,)]) * TRANS_COST_2 + FIXED_COST_2 if
ds[(0,), seq] + ds[seq, (0,)] <= DISTANCE_2 else M
)
for seq in candidate_seqs
}
route_dict = deepcopy(init_route_dict)
while True:
route_dict, new_seq_count = merge_saving_value_pairs(
candidate_seqs, route_dict, param , node_id_c,
time_sorted_limit=time_sorted_limit,
merge_seq_each_time=merge_seq_each_time
)
# update candidate seqs
candidate_seqs = list(route_dict.keys())
print("merge_seq_count: " + str(new_seq_count))
if new_seq_count < 1:
break
cost = 0
for k, v in route_dict.items():
v_ = generate_seq_info(k, param)
route_dict[k] = v_
cost += v_.cost
print(k)
print(v_)
print("final cost: " + str(cost))
save_result(route_dict, data_set_num)
i1 = route_dict.pop(seq)
route_dict[new_seq1] = new_info1
i2 = route_dict.pop(neighborhood)
route_dict[new_seq2] = new_info2
print(seq)
print(i1)
print(neighborhood)
print(i2)
print("---")
print(new_seq1)
print(new_info1)
print(new_seq2)
print(new_info2)
print("---")
print("old cost: " + str(i1.cost + i2.cost))
print("new cost: " + str(new_info1.cost + new_info2.cost))
cost = 0
for k, v in route_dict.items():
print("-" * 30)
print(k)
print(v)
new_seq, new_info = two_opt(k, v, param, best_accept=True)
print(new_seq)
print(new_info)
final_route_dict[new_seq] = new_info
cost += new_info.cost
print("-" * 20 + "\nnew cost: " + str(cost))
save_result(final_route_dict, data_set_num)