A model is a simplification of the system that is learning something useful from it, the model formalizes the system through its states and discrete events.
The system is the part of real life that the discrete event simulation is working on.
Common concepts for optimizations, whatever the technology is: Discrete event simulation, scheduling, linear programming etc.
The features of those libraries are:
- Random variable cf. def
- Pseudo-random number generator
- Main distributions:
- Time management
- Interface for time in optimization
- Implementation as Clojure date - https://github.com/dm3/clojure.java-time
- Implementation as integer, one date is a bucket number
- Implementation as variable bucket management (different bucket size)
- Scenario management
- Scenario portfolio -
- Scenario persistence -
- Optimization runner
- Randomized setup - when some parameters of the optimization are random variable
- Multiple seed execution
- Performance indicators (KPI)
- Being able to compare solutions
- Objective comparison
- Simple mono-objective comparison
- Multi-objective comparison (Pareto front)
- Time phased variable
- Generic interface - get data at a given time whatever the implementation
- Constant piecewise cf. def
- between two values: the constant piecewise is returning the value of the previous event where a constant has been set
- summing two variables: consists in two constant piecewise that are summed
- typical usage:
- stock level: a stock level is set at one point in time, and is constant and still valid for all later on moments, until next stock level information
- Dirac - the value is valid at a specific point
- between two values: 0 is returned
- summing two variables: is the union of the two sets of date/value data.
- typical usage:
- production: a production is set at one point in time, every next event does not exist
- Fuzzy interval - the value is somewhere in an interval
- between two values: the value is somewhere in between
- summing two variables: each interval intersection has a part of the value (proportional to its size), and the sum of the two intervals are stored
- typical usage:
- Demand: when a demand is set in a month, we don't really know what day it is, all zoom in should spread the value in the interval so the final total is the same
License information can be found in LICENSE file Copyright © 2020-2024 Anthony Caumond, Mateusz Mazurczak