A process-oriented and trajectory-based Discrete-Event Simulation (DES) package for R. It is designed as a generic yet powerful framework. The architecture encloses a robust and fast simulation core written in C++ with automatic monitoring capabilities. It provides a rich and flexible R API that revolves around the concept of trajectory, a common path in the simulation model for entities of the same type.
[ and [[, for trajectories (1847898). Think about trajectories as lists of activities and these operators will do (almost) everything you expect. As a side effect, the generics head() and tail() automatically work with trajectories also as expected.length() method to obtain the number of first-level activities in a trajectory (f86375a). Useful in combination with the subsetting operators.create_trajectory() has been deprecated in favor of trajectory() (76c1317).plot_resource_usage(), plot_resource_utilization(), plot_evolution_arrival_times() and plot_attributes() have been deprecated and will be removed in the next release in order to minimise dependencies (5b43f2b). We plan to release a new package on CRAN covering these features and new ones.get_head(), get_tail(), print_activity(), get_next_activity(), get_prev_activity() (f86375a). These methods were only useful for development purposes and nobody should be using them. And it was never a good idea to directly expose external pointers.renege_if() activity triggers reneging upon reception of a signal broadcasted with send() (#84).trap() (bb2aa46).set_attribute() (#82).set_queue_size() with queue_size_strict=TRUE: arrivals were not being dropped (#83).set_capacity() with a preemptive resource when the old value was Inf: arrivals were not being preempted (63beb2c).trap() printed information.set_capacity() and set_queue_size() become activities (#77). Just like seize() and release(), they have the associated set_capacity_selected() and set_queue_size_selected() for a joint use together with select().activate() and deactivate() activities allow an arrival to start or stop a generator, respectively, from inside a trajectory (#80).set_trajectory() and set_distribution() activities allow an arrival to install a new trajectory or distribution, respectively, in a generator from inside a trajectory (#80).send(), trap(), untrap() and wait() can be used to send signals, wait for signals, trap them and launch asynchronous handlers.log_() activity simply prints messages for debugging purposes (eaa4554).seize() and seize_selected() (1c8c3bb).get_mon_arrivals(ongoing = TRUE) (#73).as<>() calls (ec4e51a).run(until) runs the simulation exactly until until, instead of until the first event scheduled at a time >= until (e7264f6).priority, preemptible, restart) has been moved from seize() to add_generator() (#69). This leads to a more natural interpretation of prioritization values as attributes of arrivals from the same generator, rather than attributes of a seize(). Still, prioritization values can be redefined dynamically from inside a trajectory with the new activity set_prioritization().post.seize and reject subtrajectories in seize() and seize_selected() (#49). This feature allows us to fine-tune what happens to an arrival if it cannot seize a resource: instead of getting dropped, it may execute a given subtrajectory.clone() and synchronize() activities (#71). clone() implements the workflow pattern in which an entity is processed in multiple parallel threads. The user can define a different sub-trajectory for each clone. With synchronize(), multiple parallel clones converge and are synchronized: only one continues (the first or the last to arrive), and the others are removed.batch() and separate() activities (#45). They can be used to implement a rollercoaster process: batch() collects a number of arrivals before they can continue processing as a block, and separate() splits a previously established batch.renege_in() and renege_abort() activities (#58). They can be used to set or unset a timer after which the arrival will abandon.branch()'s option returns 0, the arrival skips the branch() and continues to the next activity instead of throwing an index out of range error (#70).every() (#65) and branch()'s deprecated argument merge (#57).join() activity to concatenate trajectories (#50).queue_size_strict to add_resource() to guarantee the queue size limit with preemption (#59).select(), seize_selected() and release_selected() activities (#52).leave() activity (#63).end_time - start_time. All versions 3.2.x are affected by this bug.preemptible in the documentation of seize() and force preemptible to be equal or greater than priority (#53).branch()'s merge parameter name to continue. The old name is deprecated (#57).match.arg() in multiple-choice arguments (#55).branch() backwards linking and count (#56).release() in two steps to deal properly with capacity changes at the same point in time (#64).every() is deprecated due to #65.capacity and queue_size can change over time following a user-defined scheduling, which can be generated with the new function schedule().?peek.plot_resource_usage() (8da9b97).merge=TRUE (#46).until=Inf is allowed now (f47baa9).t=3, queue=2 meant that, until t=3, the queue had 2 customers, and at t=3 the system changed (because of a new arrival or a new departure). The idea was to keep the values and time vectors aligned (see #28). But from this moment on, the resources are monitored _after changing the status of the system. This is more consistent with what a user would expect, and more consistent with the behaviour of other related R functions (e.g., see stepfun(), from the stats package). Wrapping up and from now on, t=3, queue=2 means that some event happened at t=3 whose immediate and subsequent result was a queue with 2 customers.preemptive=TRUE. Arrivals in the server can be preempted on a preempt_order="fifo" or preempt_order="lifo" basis. Each seize() has three basic properties:
priority: already present in previous versions.preemptible: another seize() with a priority value greater than this may preempt the present seize().restart: whether the current task (a timeout() activity, for instance) should be restarted if the arrival is preempted.show_activity() and show_trajectory().every(), to() and from_to() convenience functions (8e524cd).plot_resource_usage() (6b034a7).testthat (#41).branch() activity now provides attributes to its option function, as the other activities (#42).plot_*() functions (#44).get_mon_arrivals() returned the start/activity/end times per arrival for the whole trajectory. This behaviour remains, but additionally, get_mon_arrivals(per_resource = TRUE) returns these times per resource, so that it is possible to retrieve queueing/system times per resource.get_mon_*() functions accept a single simulation environment as well as a list of environments representing several replications (5ee2725). A new column (replication) in the resulting data frame indicates the corresponding replication number.set_attribute() activity (#16).rollback() activity (#17 and #22).self visibly, instead of invisibly (#35).at() and from() convenience functions (29cccd2 and 7cfdd90).add_skip_event() function to implement a more flexible and user-friendly branching method.n arrivals beforehand, this release leverages the concept of generator of arrivals, which is faster and more flexible. At the same time, the concept of trajectory as a chain of activities is implemented entirely in C++ internally. Our tests show that simmer is even faster than SimPy when it comes to simulate queueing networks.