between基于队列大小在pots之间重新分配资源

Question

我有一个简单的门诊部服务的工作例子。有高优先级和低优先级的病人，每个人都有一个专门的诊所。高优先级门诊每天5个时段，低优先级诊所每天1个时段。下面是测试代码：

testmixcap <- simmer()

highpriority <- trajectory("high") %>%
  log_("High priority arrival - add to wl") %>%
  select("highpclinic") %>%
  seize_selected() %>%
  log_("Attend appointment") %>%
  timeout(1) %>%
  release_selected() %>%
  log_("Discharge")

lowpriority <- trajectory("low") %>%
  log_("Low priority arrival - add to wl") %>%
  select("lowpclinic") %>%
  seize_selected() %>%
  log_("Attend appointment") %>%
  timeout(1) %>%
  release_selected() %>%
  log_("Discharge")

testmixcap %>%
  add_generator("high",highpriority,at(1,1,1,2,2,3,3,3,4)) %>%
  add_generator("low",lowpriority,at(1,1,1,1,2,2,2,3,3,3,4,4,4,5,5,6)) %>%
  add_resource("highpclinic",5) %>%
  add_resource("lowpclinic",1) 

testmixcap %>%
  run(until = 100)

testmixcap %>%
  get_mon_resources()

我的问题是，在不需要高优先级门诊时段(或不需要全部5个)的日子里，有什么方法可以告诉将其余的时段释放给低优先级资源吗？例如，高优先级诊所需要2名患者，但剩下的3名患者被添加到低优先级诊所，并通过4名患者进行治疗？

然后，诊所将需要在第二天重新调整到正常的容量，但我认为我可以用一个时间表，而不是固定的优先次序。

我认为答案在于使用信号，但我就是不能把我的头放在他们的头上。我亦曾考虑将两间诊所合并为一间诊所，并以优先次序分配给较优先的病人。但这意味着，可能会有几天，我们看到零低优先病人，这是非常不可能的。

任何感激的帮助！

Answer 1

我设法找到了一个使用全局变量的解决方案，并找到了一个假的到达生成器，它充当了一个日常监控系统，用于监测何时将过剩的容量分配给了一个高优先级的诊所。

library(simmer)
library(dplyr)

testmixcap <- simmer()

highpriority <- trajectory("high") %>%
  log_("High priority arrival - add to wl") %>%
  select("highpclinic") %>%
  seize_selected() %>%
  set_global("highpseentoday",1,"+") %>%
  log_("Attend appointment") %>%
  timeout(1) %>%
  release_selected() %>%
  log_("Discharge")

lowpriority <- trajectory("low") %>%
  log_("Low priority arrival - add to wl") %>%
  select("lowpclinic") %>%
  seize_selected() %>%
  log_("Attend appointment") %>%
  timeout(1) %>%
  release_selected() %>%
  log_("Discharge")

cap_monitor <- trajectory() %>%
  set_global("highpseentoday",0) %>% 
  timeout(0.1) %>%
  log_("Check if all today's slots used in high priority clinic") %>%
  branch(
    function(){
      seentoday <- get_global(testmixcap,"highpseentoday")
      highpcap <- get_capacity(testmixcap,"highpclinic")
      if(seentoday < highpcap) {1} else {0}
    }
    ,continue = TRUE
    ,trajectory() %>% set_capacity("lowpclinic",value = function(){
      seentoday <- get_global(testmixcap,"highpseentoday")
      highpcap <- get_capacity(testmixcap,"highpclinic")
      highpcap - seentoday
    },mod = "+")
  ) %>%
  timeout(0.9) %>%
  rollback(Inf)


testmixcap %>%
  add_generator("high",highpriority,at(1,1,1,2,2,3,3,3,4),mon = 2) %>%
  add_generator("low",lowpriority,at(1,1,1,1,2,2,2,3,3,3,4,4,4,5,5,6)) %>%
  add_resource("highpclinic",5) %>%
  add_resource("lowpclinic",schedule(c(1,2),c(1,1),2)) %>% 
  add_generator("monitor",cap_monitor,at(1))

testmixcap %>%
  run(until = 100)

testmixcap %>%
  get_mon_resources()

testmixcap %>%
  get_mon_arrivals()