Research On Discrete Particle Swarm Algorithm For Constraint Satisfaction Problems And Scheduling Problems

Constraint is an extensive concept Intuitively, a constraint is viewed as restriction in possibility space. There are plenty of examples about constraints in our everyday study lives. For instance, the time tabling of the daily classes, the scheduling of the city buses, the three angles of a triangle sum to 180 degree, etc. Generally speaking, a constraint is simply a logical relation among several unknown variables, each taking a value in a given domain. Constraints are used to model the behavior of systems of objects in the real world by capturing an idealized view of the interaction among the objects, this called constraint modeling. It is the category of constraint programming to simplify a real world situation into a system of constraints about idealized objects, and use this system of constraints to better understand the behavior of the real world. Constraint programming is the study of computational systems based on constraints, is a powerful method on programming, modeling and problem resolution.The Constraint Satisfaction Problem (CSP) is used to model general finite constraint domains. It comprises a finite set of variables, each variable has finite domain, a finite set of constraints. Each constraint restricts the combination of values that a set of variables can take simultaneously. A solution of a CSP is an assignment to each variable a value from its domain satisfying all the constraints. The target of a CSP is to find one solution or all solutions. The search methods to CSP always are systematic search algorithms, e.g. generate and test, backtracking, constraint propagation, etc.Scheduling problem in fact is to allocate resources reasonably in a certain time level so that we can reach the predefine target. Many researches have been done over the past decades years on the scheduling problems, and the importance of scheduling problem is recognized by the scientists cover the mathematics, operation research and engineering. Scheduling has been applied in number of areas such as job planning, enterprise management, traffic, astronautics, medical treatment, flexible manufacturing system, etc. The solving techniques for scheduling problem include linear programming, integer programming, target programming, dynamic programming and decision-making. They are used broadly and make big success.The constraint solving techniques have had tremendous influence upon our whole...