func calculate_plus_cost(matrix tsp_types.MatrixType, n int) (bool, tsp_types.DataType) {
cost := tsp_types.DataType(0)
// every row
for i := 0; i < n; i++ {
min_value := tsp_types.POSITIVE_INF
// looking min value in row
infinity_count := 0
for j := 0; j < n; j++ {
if matrix[i*n+j] == tsp_types.POSITIVE_INF {
infinity_count++
} else if matrix[i*n+j] < min_value {
min_value = matrix[i*n+j]
}
}
// if all elements in row are infinite then return
if infinity_count == n {
return false, tsp_types.DataType(0)
}
if min_value != 0 {
// subtract min value from entire row
for j := 0; j < n; j++ {
if matrix[i*n+j] != tsp_types.POSITIVE_INF {
matrix[i*n+j] -= min_value
}
}
// add min value to cost
cost += min_value
}
}
// every collum
for i := 0; i < n; i++ {
min_value := tsp_types.POSITIVE_INF
// looking min value in collum
infinity_count := 0
for j := 0; j < n; j++ {
if matrix[j*n+i] == tsp_types.POSITIVE_INF {
infinity_count++
} else if matrix[j*n+i] < min_value {
min_value = matrix[j*n+i]
}
}
// if all elements in collum are infinite then return
if infinity_count == n {
return false, tsp_types.DataType(0)
}
if min_value != 0 {
// subtract min value from entire column
for j := 0; j < n; j++ {
if matrix[j*n+i] != tsp_types.POSITIVE_INF {
matrix[j*n+i] -= min_value
}
}
// add min value to cost
cost += min_value
}
}
return true, cost
}
func listen_server(conn *net.Conn, logger *log.Logger, curr_task_info *CurrTaskInfo) {
for {
var data_size int64
err := binary.Read(*conn, binary.LittleEndian, &data_size)
if err != nil {
logger.Printf("Reading data size (client) error: %v\n", err)
return
}
if log_enable {
logger.Printf("Read new data\n")
} else {
fmt.Printf("\n")
}
data := make([]byte, data_size)
_, err = (*conn).Read(data)
switch string(data[0]) {
case "q":
return
case "m":
param_vec := strings.Split(string(data[1:]), " ")
if len(param_vec) != 2 {
logger.Println("min cost error: param count != 2")
return
}
task_id, err := strconv.Atoi(param_vec[0])
if err != nil {
logger.Printf("task id convert error: %v\n", err)
return
}
min_cost, err := strconv.Atoi(param_vec[1])
if err != nil {
logger.Printf("min cost convert error: %v\n", err)
return
}
if curr_task_info.TaskID < 0 {
curr_task_info.TaskID = task_id
curr_task_info.MinCost.Set(tsp_types.DataType(min_cost))
} else if task_id == curr_task_info.TaskID {
curr_task_info.MinCost.Set(tsp_types.DataType(min_cost))
}
default:
task_str := string(data[1:])
sep_index := strings.Index(task_str, " ")
new_task_id, err := strconv.Atoi(task_str[:sep_index])
if err != nil {
logger.Printf("curr task id convert error: %v\n", err)
return
}
curr_task_info.TaskID = new_task_id
go solve_task(task_str[sep_index+1:], conn, logger, curr_task_info)
}
}
defer (*conn).Close()
}
func find_heavier_zero(matrix tsp_types.MatrixType, n int) tsp_types.ZeroInfoType {
heavier_zero := tsp_types.ZeroInfoType{0, 0, tsp_types.NEGATIVE_INF}
for i := 0; i < n; i++ {
// for every zero in row
for j := 0; j < n; j++ {
if matrix[i*n+j] == 0 {
// find min element in row
weight := tsp_types.DataType(0)
min_value := tsp_types.POSITIVE_INF
for z := 0; z < n; z++ {
if (z != j) && (matrix[i*n+z] < min_value) && (matrix[i*n+z] != tsp_types.POSITIVE_INF) {
min_value = matrix[i*n+z]
}
}
if min_value != tsp_types.POSITIVE_INF {
weight += min_value
}
// find min element in collum
min_value = tsp_types.POSITIVE_INF
for z := 0; z < n; z++ {
if (z != i) && (matrix[z*n+j] < min_value) && (matrix[z*n+j] != tsp_types.POSITIVE_INF) {
min_value = matrix[z*n+j]
}
}
if min_value != tsp_types.POSITIVE_INF {
weight += min_value
}
// remember new zero
if heavier_zero.Weight < weight {
heavier_zero = tsp_types.ZeroInfoType{i, j, weight}
}
}
}
}
return heavier_zero
}
