我正在尝试使用loco进行优化的基本示例。
我有一个成本向量,其索引对应于多个时隙的整数值,并且希望最小化不同时隙子集的成本总和。
请参阅下面我的尝试,但由于所选插槽与费用之间没有“链接”,因此无效。
(def costs [10 10 20 20 30 30 40 40 10 10])
(let [slot-vars (for [i (range 5)] ($in [:slot i] 1 10))
cost-vars (for [i (range 10)] ($in [:cost i] 10 40))]
(solution
(concat
slot-vars
cost-vars
[($distinct (for [i (range 5)] [:slot i]))]
(for [i (range 5)]
($= [:cost i] (get costs i))))
:minimize (apply $+ (for [i (range 5)] [:slot i]))))
答案 0 :(得分:2)
这不是答案,但我希望它可能有助于指出可能有所帮助的方向。这听起来像背包问题?
您可以找到最大值:
(def slots (for [i (range 10)] (keyword (str "slot-" i))))
(solution
(concat
(for [s slots] ($in s 0 1))
[($in :total-weight 10 60)
($in :total-value 5 5)
($knapsack [10 10 20 20 30 30 40 40 10 10]
(repeat 10 1)
slots :total-weight :total-value)]))
假设你只能有5个插槽。
可以通过查看源代码并直接使用Choco库来编写最小化版本吗?
检查loco knapsack函数的来源。
答案 1 :(得分:2)
首先,我不完全确定我理解这个问题的关键点,因为显然解决方案是只取列表中的5个最小值。但是如果你想让loco这样做,我同意背包约束是一个方便的工具。与Mike在评论中所说的相反,我认为使用背包进行最小化并没有任何障碍。让权重都为1,并强制权重加起来为5,以便从10个槽中选择5个。我已经使用变量[:include i]
来指示插槽i是否应该包含在子集中(1表示true,0表示false)。我们希望最小化向量的点积:包括变量和成本向量。
(def costs [10 10 20 20 30 30 40 40 10 10])
(def weights (repeat 10 1))
(def include-vars (for [i (range 10)] [:include i]))
(def include-constraints (for [i (range 10)] ($in [:include i] 0 1)))
(def model
(concat
include-constraints
[($knapsack weights costs include-vars 5 :total)
($in :total 0 (apply + costs))]))
(solution model :minimize :total)
结果是:
{[:include 4] 0, [:include 6] 0, [:include 9] 1, [:include 1] 1, [:include 3] 0, [:include 8] 1, :total 60, [:include 0] 1, [:include 7] 0, [:include 2] 1, [:include 5] 0}