A Novel Sequential Quadratic Programming Based Material Allocation Optimization Algorithm

Abstract

Material allocation is a nonlinear optimization problem. For this problem, a quadratic programming based material allocation optimization algorithm is proposed. In the proposed algorithm, firstly, the objective function of support effectiveness and its approximate model of quadratic programming are constructed with target importance and material requirements. Secondly, by using SQP (sequential quadratic programming), the proposed algorithm quickly converge to the optimal solution. For the initial allocation, selective rounding and iterative adjustment according to the material requirements is implemented, and then obtaining the final allocation. Simulation results show that through combing the target parameters and actual requirements constrains, the proposed algorithm can realize reasonable, balanced and fast allocation.