Abstract
Materials acquisition is one of the critical challenges faced by academic libraries. This paper presents an integer programming model of the studied problem by considering how to select materials in order to maximize the average preference and the budget execution rate under some practical restrictions including departmental budget, limitation of the number of materials in each category and each language. To tackle the constrained problem, we propose a discrete particle swarm optimization (DPSO) with scout particles, where each particle, represented as a binary matrix, corresponds to a candidate solution to the problem. An initialization algorithm and a penalty function are designed to cope with the constraints, and the scout particles are employed to enhance the exploration within the solution space. To demonstrate the effectiveness and efficiency of the proposed DPSO, a series of computational experiments are designed and conducted. The results are statistically analyzed, and it is evinced that the proposed DPSO is an effective approach for the studied problem.
Highlights
In recent years, the price inflation of library materials, the shrinking of library budget, and the growth of electronic resources continue to challenge the acquisition librarians [1]
The three rows in each table report the number of observations on the results of different discrete particle swarm optimization (DPSO) algorithms for the test instances, the z-score of statistical test where the null hypothesis is that the different features of DPSO algorithm have the same improvement, and the P value which is translated from z-score
We have proposed an integer programming model for the materials acquisition problem, which is to maximize both the average preference and the budget execution rate being subject to some constraints of the budget, the required number of materials in each category and language
Summary
The price inflation of library materials, the shrinking of library budget, and the growth of electronic resources continue to challenge the acquisition librarians [1]. Arora and Klabjan [9] point out the critical concern about fairness in materials acquisition of academic libraries They provide a model for maximizing the usage in the future time period subject to the bounds on the number of materials of each category and the lower and the upper bounds on the budgets of the library units. This study will investigate the scenario where each individual department has its own budget limit for the preferred materials that are to be acquired This type of budget plan will introduce financial constraints that are much more complicated. We concentrate on how to select materials to be acquired in order to maximize the average preference as well as the budget execution rate under the real-world restrictions including departmental budget and limitation of the number of materials in each category.
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