The purpose of this page on Constraint Optimisation is to give a brief overview of Constraint Optimisation from a business director perspective.
Constraint Optimisation (CO) is a technology for determining the best possible utilisation of resources (e.g. time, people, processes, raw materials, supplies, securities, etc.) required to achieve a desired business outcome (minimum cost, minimum process time, maximum profit, etc.).
Constraint Optimisation uses a set of techniques – such as Constraint Programming, Linear Programming and Mathematical Programming – to maximise or minimise an objective function, subject to a satisfying a set of potentially conflicting hard and soft constraints. A hard constraint must be met by a solution whereas a soft constraint only expresses a preference in a possible solution.
Traditionally Constraint Optimisation has been used for scheduling and resource allocations for problems in areas such as transportation, supply chain, logistics, airline scheduling, and it is now ready to be used across the enterprise to reduce costs, and increase revenues and business agility.
Constraint Optimisation can now be extended by the hybrid integration of business rule engines and business optimisation engines. In this approach the rule engines (acting as decision services) are used to set the context and space of the business problems, at which point the business optimisation engines are called to find an optimal solution.