Using Simulated Annealing for Efficient Allocation of Students to Practical Classes

Abstract

This paper is concerned with the development of a simulated annealing algorithm to schedule computer practical classes in a university environment. The main objective is to minimise the number of classes needed in order to allocate each student to a class at a time which he or she can attend, subject to a capacity constraint on the computer laboratory. This problem is encountered each year in the European Business Management School at Swansea University, U.K.. The diversity of the lecture timetables of the students involved mean that is difficult to find a set of suitable times which cover all the students, and the problem is further complicated by the presence of a number of secondary objectives. A solution based on a simulated annealing algorithm in which the cost function is updated as new information becomes available during the search is developed. Computational experience based on real data from the last two years shows that this algorithm is flexible enough to deal effectively with both primary and secondary objectives.