func start_worker(worker_id int) {
logger := log.New(os.Stdout, fmt.Sprintf("WORKER(%d): ", worker_id), log.Ldate|log.Ltime)
gl_min_cost := tsp_types.GlobalCostType{}
gl_min_cost.Init(tsp_types.POSITIVE_INF)
curr_task_id := -1
runtime.GOMAXPROCS(runtime.NumCPU())
destination := "127.0.0.1:5000"
logger.Println("worker: connect to ", destination)
conn, err := net.Dial("tcp", destination)
if err != nil {
logger.Printf("dial error: %v", err)
}
curr_task_info := CurrTaskInfo{curr_task_id, gl_min_cost}
go listen_server(&conn, logger, &curr_task_info)
}
func SolveImpl(task tsp_types.TaskType, gl_min_cost *tsp_types.GlobalCostType) (tsp_types.AnswerType, bool) {
if gl_min_cost.Get() < task.MinCost {
return tsp_types.ERROR_ANSWER, false
}
if (task.Size == 0) || (task.Size == 1) {
return tsp_types.ERROR_ANSWER, true
}
success, additional_cost := calculate_plus_cost(*task.Matrix, task.Size)
if !success {
return tsp_types.ERROR_ANSWER, true
}
task.CurrCost += additional_cost
heavier_zero := find_heavier_zero(*task.Matrix, task.Size)
// if task.Size is 2 end recursion
if task.Size == 2 {
next_city := heavier_zero.Col
previous_city := heavier_zero.Row
if ((*task.Matrix)[(previous_city^1)*2+(next_city^1)] == 0) &&
((*task.Matrix)[(previous_city^1)*2+next_city] == tsp_types.POSITIVE_INF) &&
((*task.Matrix)[previous_city*2+(next_city^1)] == tsp_types.POSITIVE_INF) {
jumps := make([]tsp_types.JumpType, 2)
jumps[0] = tsp_types.JumpType{task.RowMapping[heavier_zero.Row], task.ColMapping[heavier_zero.Col]}
jumps[1] = tsp_types.JumpType{task.RowMapping[heavier_zero.Row^1], task.ColMapping[heavier_zero.Col^1]}
for j := range task.Jumps {
jumps = append(jumps, task.Jumps[j])
}
return tsp_types.AnswerType{jumps, task.CurrCost}, true
} else {
return tsp_types.ERROR_ANSWER, true
}
}
// prepare data for recursive call
sub_dt := generate_sub_task_data(task.Matrix, task.RowMapping, task.ColMapping, task.Jumps, heavier_zero, task.Size)
//call this function recursively
answer, less_global := SolveImpl(tsp_types.TaskType{sub_dt.Matrix, sub_dt.RowMapping, sub_dt.ColMapping, sub_dt.Jumps, task.CurrCost, task.MinCost, task.Size - 1}, gl_min_cost)
if !less_global {
return tsp_types.ERROR_ANSWER, false
}
//print_answer(answer, "GOT ANSWER")
final_path := []tsp_types.JumpType{}
if answer.Cost < task.MinCost {
final_path = answer.Jumps
task.MinCost = answer.Cost
}
//right_path
if (task.CurrCost + heavier_zero.Weight) < task.MinCost {
//correct first one
(*task.Matrix)[heavier_zero.Row*task.Size+heavier_zero.Col] = tsp_types.POSITIVE_INF
answer, less_global = SolveImpl(task, gl_min_cost)
if !less_global {
return tsp_types.ERROR_ANSWER, false
}
if answer.Cost < task.MinCost {
final_path = answer.Jumps
task.MinCost = answer.Cost
}
}
// return answer
if task.MinCost < tsp_types.POSITIVE_INF {
return tsp_types.AnswerType{final_path, task.MinCost}, true
} else {
return tsp_types.ERROR_ANSWER, true
}
}
