Discrete Particle Swarm Optimization for Materials Budget Allocation in Academic Libraries

Abstract

We formulate the problem of materials budget allocation for academic libraries by way of the mathematical programming model and design an effective algorithm using discrete particle swarm optimization to resolve the problem. The objective function is to maximize the average preferences of materials selection subjected to the constraints of material costs and required amounts in specified categories. For the comparison purpose, CPLEX, a linear programming software package, and a greedy algorithm are applied to obtain optimal or approximate solutions. The computation results demonstrate the effectiveness and robustness of the proposed DPSO algorithm in dealing with the materials budget allocation problem.