Optimize rules are defined to implement the scheduling objective in APS. That is, when an optimization is performed, APS’s optimization engine allocates resources according to the preferences defined here. For example, APS can optimize with the objective to minimize costs or maximize efficiency.

Most of the different rules are included in APS’ standard library of rules. The ability to group jobs together by Material Item or to schedule according to Operation Attributes provides the user with additional flexibility and depth in creating an accurate model.

Key Concepts

Optimize rules are prioritized according to a system of relative weights. A higher relative weight marks a specific rule as being of greater importance while a lower weight marks it as being secondary or tertiary. It’s important to remember that the weights are relative – assigning two rules with the same high weight is no different than assigning the same two rules with identical lower weights.

When balancing different rules, keep in mind that many of the rules produce a sort of “apples to oranges” comparison. The Ranges portion of the Optimize Rule screen allows the user to normalize the different weights, providing a simple table of equivalence between the different factors being considered during the optimize process. This is particularly helpful when optimize rules must be precise such as when the manufacturer has quantifiable data or scheduling algorithms that must be modeled in order for a successful project.

The optimize rules need to be assigned to the appropriate resources. There can be two different optimize rules associated with each resources, the “Normal optimize rule” and “Experimental optimize rule”. Using Optimize options’ Rules tab the planner can choose which rule to use when optimizing. It’s also important to note that while each individual Resources may have their own Optimize Rule, the entire Plant can also be set to use a specific rule in simpler setups.