Take, for example, a transport company that is to supply 500 televisions to 10 different locations with only 3 trucks at its disposal and within a certain period of time. I don't think it's so easy to manually map out the best possible route for this, right?
Another example. 200 nurses who have to be divided into their shifts, taking into account contractual obligations and the wishes of the nurses themselves. Combined with the law of nature that says that a nurse can, of course, not practice 2 shifts at the same time, this again does not seem to be a simple planning that needs to be made.
In short, tackling such problems manually requires very time-consuming and intensive efforts, which are far from reaching the optimum level possible. But is it possible to achieve the optimum level? A solution is almost never optimal, but we can make sure that we generate the best possible solution within a certain time. How do you ask? Well, the Optaplanner software is the most suitable candidate for this.
What started out as a hobby soon grew into the world's best business resource optimizer. Geoffrey De Smet is Optaplanner's father and soon, after taking part in several competitions with his implementation, realized that he had a rough diamond that could lead to a new era in the optimization of business resources. Sponsored by Red Hat, Geoffrey and his team work on a daily basis on sharpening this rough diamond by generating new features which can master the modelling and solving of any kind of problem.
All of this may sound promising, but how does Optaplanner work correctly? This Technology uses metaheuristic algorithms and an effective scoring system that takes the scheduling of all kinds of business resources to the optimum level. The constraints of business rules form part of the basis of OptaPlanner and ensure that a planning will not deviate from certain criteria. Constraints are defined as hard and soft constraints in which the soft constraints can be both negative and positive and the hard constraints only negative.