//登山法优化
func optimizeHillClimb(domainList [][2]int, costF func([]int) int64) []int {
	var bestSchedule []int
    
	fmt.Println(domainList)
	r := rand.New(rand.NewSource(time.Now().UnixNano()))
	for _, domain := range domainList {
		choice := r.Intn(domain[1] - domain[0]) + domain[0]
		bestSchedule = append(bestSchedule, choice)
	}
    
	//Main loop
	for {
		//Create list of neighboring solutions
		var neighbors [][]int
		fmt.Println("start", bestSchedule)
    
                 //One away in each direction
		for i := 0; i < len(domainList); i ++ { 
                        if bestSchedule[i] > domainList[i][0] {
				newSchedule := make([]int, len(bestSchedule))
				copy(newSchedule, bestSchedule)
				newSchedule[i] = bestSchedule[i]-1
				neighbors = append(neighbors, newSchedule)
			}
			if bestSchedule[i] < domainList[i][1] {
				newSchedule := make([]int, len(bestSchedule))
				copy(newSchedule, bestSchedule)
				newSchedule[i] = bestSchedule[i]+1
				neighbors = append(neighbors, newSchedule)
			}
		}
    
		//See what the best solution amongst the neighbors is
		current := costF(bestSchedule)
		best := current
		for j := 0; j < len(neighbors); j ++ {
			cost := costF(neighbors[j])
			//fmt.Println("neighbors", neighbors[j], cost)
			if cost < best {
				best = cost
				bestSchedule = neighbors[j]
			}
		}
    
		//If there's no improvement, then we've reached the top
		if best == current {
			break
		}
		fmt.Println("best", bestSchedule)
	}
    
	return bestSchedule
}