Atificial Imune Agorithm And Its Apllication In Timetable System

The timetabling has always been a necessary job for the administrative work ofuniversities. With the constantly development of high education, course arranging problem hasvery important role in training students and rising the education quality. Along with theincreasing number of students the course arranging is becoming a particularly hard and keyteaching supervisory work. Schedule-arranging is a very complicated schedule problem. It isalso a NP-Complete (Non-deterministic Polynomial Time) problem. So far, the NP-Complete isa function is a kind of exponential function which is best way to solve multiple restrictions,including the restrictions of teachers, students, teaching facility and course time. All therestrictions try to be satisfied in order to get the optimum. It is a very complicated problem dueto the consideration of many factors and restrictions. Although many computer-based solutionshave been proposed in the literature, none of them can be universally applied to eachdepartment.Artificial immune systems are kinds of intelligence approaches that simulate somefunction of nature immune systems. Among the artificial immune systems, clonal selectionalgorithm has been attracting long-drawn attention, more and more clonal selection algorithmshave been proposed. In this paper, based on the simulation of the biological immune system andan investigation into the timetable schedule, we introduce a new approach named cloneStrength Pareto Algorithm, which introduces clonal selection algorithms into this multiobjectiveoptimization problem. Using the Delphi6.0of Borland company, we develop a clone StrengthPareto Algorithm, which provide the input, edit, schedule of timetable. In this paper, this newalgorithm is compared quantitatively with five former multiobjective optimization algorithms.The results show that it can not only achieve the multiple constraints of timetable schedule, andis superior to the other multiobjective optimization algorithms.