PlanningForce facilitates the organization of different tasks (fragmentable or not, repetitive, etc.) by taking into account time constraints, precedence constraints, synchronization and resource constraints (staff, equipment, renewable, consumables, limited availability, …).
The produced plan must be able to answer the following questions precisely: who? what? where? when? how? how much?
This Resource Constrained Project Scheduling Problem (RCPSP) is one of the so-called ‘NP-complete’ problems, i.e. the only known method to find the optimal solution is to make a complete enumeration of all possible solutions.
However, as soon as they reach a medium size, companies are quickly confronted with the need to plan several thousand tasks. In such a context, trying to build the best solution (global optimum) would therefore be prohibitively expensive both in terms of computing time and the stability of the solution found.
In order to solve this problem, PlanningForce has developed and implemented approximate methods, operational research techniques (graph theory, critical path, weighted oriented graph, constructive heuristics, serial methods, meta-heuristics, local search, backtracking, decision trees, etc.) and specific algorithms (adapted prioritization of criteria and constraints).
Thanks to its tools, its algorithms, their skillful combination and its strong ability to describe a problem (what we call “problem modeling”), PlanningForce analyzes the data (tasks, resources, constraints) and then chooses, for each task, a combination of methods to position it in the schedule as if the user had done so manually.
This three-step approach to resolution:
- Modeling the problem (as opposed to programming it ‘hard’)
- Differentiated analysis of different planning contexts by type of task or problem identified
- The application of a combination of techniques to the different contexts, chosen according to user experience
gives PlanningForce its main characteristics and differentiating elements, namely
- Flexibility and speed in describing problems
- Speed of finding solutions
- Relevance and ‘intelligibility’ of the solutions produced
- Stability of solutions
- Ability to generate numerous simulations by modifying master data (e.g., prioritizing projects, adding resources, modifying competency profiles, etc.).
The PlanningForce algorithm is the result of more than 20 years of inspired work. The process was initiated and led by Frédéric Dufour and Gaetan Libert. Throughout these developments, the algorithmic part remained the responsibility and operational fact of the two founders.
Between the years 2000 and 2011, the algorithm was developed independently from the PlanningForce software itself. After the year 2011, the algorithm was incorporated into the software package, PlanningForce.
The entirety of the algorithm’s development lasted 11 years. Since 2012, regular improvements have been made on the basis of practical analyses in the form of feedback emanating from the field, but the foundation of the algorithm has not been altered.
The main feature that the PlanningForce software boasts is its algorithm; its “planning and scheduling engine”. This is what makes it unique. The brand image of PlanningForce is in fact inseparable from its “algorithmic planning and scheduling engine”.