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我對線性優化很陌生,我想將其應用於經典的調度問題。對於人員配置問題,我不太清楚如何聲明捕捉正在採取的「轉變」概念的功能。ojAlgo線性優化 - 防止工作班次重疊?
我使用的ojAlgo迄今爲止一直非常棒。這是我想出的小問題,我想出了:
SCENARIO:
You have three drivers to make deliveries.
Driver 1 costs $10/hr
Driver 2 costs $12/hr
Driver 3 costs $14/hr
Each driver can only work 3-6 hours a day.
Only one shift can be worked by a worker a day.
Operating day is 6:00 to 22:00, which must be fully covered.
Driver 2 cannot work after 11:00.
Create a schedule that minimizes the cost.
Solve Variables:
Tsx = shift start for Driver X
Tex = shift end for Driver X
Minimize:
10(Te1 - Ts1) + 12(Te2 - Ts2) + 14(Te3 - Ts3)
10Te1 - 10Te2 + 12Te2 - 12Ts2 + 14Te3 - 14Ts3
Constraints:
4.0 <= Te - Ts <= 6.0
6.0 <= Ts, Te <= 22.0
(Te1 - Ts1) + (Te2 - Ts2) + (Te3 - Ts3) = (22.0 - 6.0)
Te2 <= 11
這是我把它放在一起的Kotlin代碼。我發現每個Driver
實例都可以更輕鬆地處理儘可能多的功能輸入(通過OOP產生了一些有趣的模式)。
import org.ojalgo.optimisation.ExpressionsBasedModel
import org.ojalgo.optimisation.Variable
fun main(args: Array<String>) {
val model = ExpressionsBasedModel()
val drivers = sequenceOf(
Driver(1, 10.0, model),
Driver(2, 12.0, model),
Driver(3, 14.0, model)
).map { it.driverNumber to it }
.toMap()
model.addExpression("EnsureCoverage")
.level(16.0)
.apply {
drivers.values.forEach {
set(it.shiftEnd, 1)
set(it.shiftStart, -1)
}
}
model.addExpression("Driver2OffAt11")
.upper(11)
.set(drivers[1]!!.shiftEnd, 1)
val result = model.minimise()
println(result)
}
data class Driver(val driverNumber: Int,
val rate: Double,
val model: ExpressionsBasedModel) {
val shiftStart = Variable.make("${driverNumber}shiftStart").weight(rate).lower(6).upper(22).apply(model::addVariable)
val shiftEnd = Variable.make("${driverNumber}shiftEnd").weight(rate).lower(6).upper(22).apply(model::addVariable)
init {
model.addExpression("${driverNumber}shiftLength")
.lower(4.0)
.upper(6.0)
.set(shiftEnd, 1)
.set(shiftStart, -1)
}
}
但我得到這個輸出表明所有三個驅動程序分配在上午6:00並同時工作。司機1從6:00-11:00,司機2從6:00-12:00,司機3從6:00-11:00。
OPTIMAL 624.0 @ [6.0, 11.0, 6.0, 12.0, 6.0, 11.0]
我不希望它們重疊。我一次只需要分配一名司機,我希望整個工作日都能得到滿足。我如何表達已經佔用時間的二進制狀態?
這裏是一個類似的問題[[鏈接]的一個例子(http://yetanothermathprogrammingconsultant.blogspot.com/2017/03/employee-scheduling-iv- direct.html)。它與替代方案和方法有關。 –
這是一個建模問題,並不是專門針對ojAlgo的。如果你的谷歌調度和/或分配問題,你會發現有很多要閱讀。 – apete