Scientific journals, conferences, and an arsenal of different solving techniques Solving large, real-world scheduling problems.ĬP has a widespread and very active community around the world with dedicated The CP method keeps track of which solutions remainįeasible when you add new constraints, which makes it a powerful tool for Solutions - for example, that each employee works at least a minimum Usually there will be other constraints that reduce the number of feasible Is huge: each day, there are 4! = 4 * 3 * 2 * 1 = 24 possible employeeĪssignments, so the number of possible weekly schedules is 24 7, which Even in such a small case, the number of possible schedules Three of its four employees to different shifts each day, while giving theįourth the day off. Very simple example: a company runs three 8-hour shifts per day and assigns The problem arises when companies that operate continuously - such asįactories - need to create weekly schedules for their employees. Large set of possible solutions to a more manageable subset by addingĪn example of a problem that is well-suited for CP is employee scheduling. Have an objective function - the goal may simply be to narrow down a very Variables rather than the objective function. Optimization (finding an optimal solution) and focuses on the constraints and , rather than programming in a computer language.)ĬP is based on feasibility (finding a feasible solution) rather than Here, "programming" refers to the arrangement of a plan "programming" is a bit of a misnomer, similar to how "computer" once meant Set of candidates, where the problem can be modeled in terms of arbitraryĬP problems arise in many scientific and engineering disciplines.
(CP), is the name given to identifying feasible solutions out of a very large
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