Material Acquisitions in Academic Libraries

As the population of books and other materials increases explosively, an effective plan for material acquisitions becomes an emergent and significant need for most modern academic libraries. However, there are few researches on this topic in the past decades. We thereby propose a formal model for material acquisitions that resembles the practical situations of academic libraries. In the proposed model, we consider several features for each material (including the preference, price and its categories) as well as the budget for each category. The goal is to select materials to achieve a maximum total preference under the constraint that the acquisition for each category of materials is controlled by a predefined budget. With the computational complexity of the studied problem, we seek to produce approximate solution in a reasonable time. Three meta-heuristics, namely simulated annealing, genetic algorithm and tabu search, are developed to cope with this problem. Computational results reveal that tabu search is the most elegant approach among the three for the material acquisitions problem.