//parSize 粒子数
//maxIter 迭代数
//step    速度的跨度
func optimizeParticleSwarm(domainList [][2]int, costF func([]int) int64, parSize, maxIter, step int) []int {
	dim := len(domainList)
	parScheduleList := make([][]int, 0)//单个位置的列表
	parVelocityList := make([][]int, 0)//单个速度的列表
	parCostList := make([]int64, 0)//单个最优值的列表
	parBestScheduleList := make([][]int, 0)//单个最优解的列表
	var globalCost int64 = 999999//全局最优值
	globalSchedule := make([]int, 0) //全局最优解
	var w float64 = 0.5
	var c1 float64 = 2.0
	var c2 float64 = 2.0
    
	fmt.Println(domainList)
	r := rand.New(rand.NewSource(time.Now().UnixNano()))
	//Build the initial
	for i := 0; i < parSize; i ++ {
		var initSchedule []int
		for _, domain := range domainList {
			choice := r.Intn(domain[1] - domain[0] + 1) + domain[0]
			initSchedule = append(initSchedule, choice)
		}
		parScheduleList = append(parScheduleList, initSchedule)
		parBestScheduleList = append(parBestScheduleList, initSchedule)
    
		var initVelocity []int
		for j := 0; j < dim; j ++ {
			choice := r.Intn(3 * step) - step
			initVelocity = append(initVelocity, choice)
		}
		parVelocityList = append(parVelocityList, initVelocity)
    
		parCostList = append(parCostList, costF(initSchedule))
    
		if globalCost > parCostList[i] {
			globalCost = parCostList[i]
			//globalSchedule = initSchedule
			globalSchedule = make([]int, 0)
			for j := 0; j < dim; j ++ {
				globalSchedule = append(globalSchedule, initSchedule[j])
			}
		}
	}
	fmt.Println("parScheduleList", parScheduleList)
	fmt.Println("parVelocityList", parVelocityList)
	fmt.Println("globalCost", globalCost)
	fmt.Println("globalSchedule", globalSchedule)
    
	//Main loop
	for x := 0; x < maxIter; x ++ {
		fmt.Println("loop", x)
		//update
		for i := 0; i < parSize; i ++ {
			fmt.Println("bird", i)
			for j := 0; j < dim; j ++ {
				parVelocityList[i][j] = int(w*float64(parVelocityList[i][j]) + c1*r.Float64()*float64(parBestScheduleList[i][j]-parScheduleList[i][j]) + c2*r.Float64()*float64(globalSchedule[j]-parScheduleList[i][j]))
				//要不要限制速度
				if parVelocityList[i][j] < -4 {
					parVelocityList[i][j] = -4
				}
				if parVelocityList[i][j] > 4 {
					parVelocityList[i][j] = 4
				}
    
				parScheduleList[i][j] = parScheduleList[i][j] + parVelocityList[i][j]
				if parScheduleList[i][j] < domainList[j][0] {
					parScheduleList[i][j] = domainList[j][0]
				}
				if parScheduleList[i][j] > domainList[j][1] {
					parScheduleList[i][j] = domainList[j][1]
				}
			}
			//fmt.Println("parVelocityList", parVelocityList[i])
			//fmt.Println("parScheduleList", parScheduleList[i])
    
			//get pBest
			if cost := costF(parScheduleList[i]); parCostList[i] > cost{
				parCostList[i] = cost
				parBestScheduleList[i] = parScheduleList[i]
				fmt.Println("parCostList", parCostList[i])
				fmt.Println("parBestScheduleList", parBestScheduleList[i])
			}
    
			//get gBest
			if globalCost > parCostList[i] {
				globalCost = parCostList[i]
				//globalSchedule = parBestScheduleList[i]
				globalSchedule = make([]int, 0)
				for j := 0; j < dim; j ++ {
					globalSchedule = append(globalSchedule, parBestScheduleList[i][j])
				}
				fmt.Println("globalCost", globalCost)
				fmt.Println("globalSchedule", globalSchedule, costF(globalSchedule))
			}
		}
	}
    
	fmt.Println("best", globalCost)
	fmt.Println("bestSchedule", globalSchedule)
	return globalSchedule
}