An evolutionary approach to library materials acquisition problems
This paper studies a library materials problem in which materials are served for satisfying the information need of its patrons. The objective is to maximize the average preferences of acquired subjects. We first formulated the problem by means of the mathematical programming. Without loss of generality, some empirical constraints are considered, including subject costs and the required amount of specified disciplines. We then design a particle swarm optimization to resolve the problem. CPLEX, a linear programming software package, was used to break down the small problems and provided optimal solutions for comparison. Computational results show that the proposed algorithm can optimally solve problems within a reasonable amount of time.