The five supply chain optimization technologies at the core of DELMIA Quintiq Optimizers are:
Quill is the proprietary configuration language at the center of the DELMIA Quintiq Optimizer. It allows easy expression of construction heuristics and local search heuristics –closely matching the processes that human planners follow when they build solutions from scratch and when they locally improve solutions. Quill is the glue that holds all the optimization technologies together, allowing them to work as an effective, efficient whole.
- Mathematical Programming
Based on decades of operations research, mathematical programming is the de facto standard for solving problems that can be expressed or approximated with linear equations. For example, it’s used in DELMIA Quintiq Workforce Planner to determine the best possible combination of tasks to assign to employees to ensure the best use of each person’s skills and achieve the highest possible service levels.
- Constraint Programming
Constraint programming is effective in dealing with particularly challenging optimization problems. It works by eliminating potential solutions through sophisticated constraint propagation, thus allowing a wide variety of constraint types. It has effective in solving heavily constrained scheduling problems.
- Path Optimization Algorithm
Path optimization algorithm is a proprietary large-neighborhood-search (LNS) technology. LNS explores much larger neighborhoods than local search and as such is less likely to get stuck in a locally optimal solution that is far from the globally optimal solution. It is primarily used for vehicle routing and manufacturing scheduling. For example, it’s used in DELMIA Quintiq Logistics Planner to determine the best possible sequence of visits and their distribution over routes to ensure the shortest distance, lowest cost and highest service level.
- Graph Programming
Many practical puzzles have a graph component and accordingly we utilize graph programming to find solutions. Graph programming is used to tackle resource-constrained shortest-path problems encountered in puzzles such as crew diagramming and rolling stock optimization.