Dynamic resource allocation and collaborative scheduling in R&D and manufacturing processes of high-end equipment with budget constraint

Abstract

This paper investigates the collaborative scheduling problem of research and development (R&D) and manufacturing processes in the context of high-end equipment, and the objective is to minimize the makespan. A unique feature is the dual usage of a limited resource budget, which can increase the quantity of both researchers and assembly lines. This brings new challenges to resource allocation and related collaborative scheduling. A mixed-integer programming model is formulated and further simplified based on the network structure, and the CPLEX solver is used to obtain the optimal solutions for the simplified model with the small-scale cases. Furthermore, an improved Variable Neighborhood Search (IVNS) algorithm is developed to obtain the near-optimal solutions for small-scale and large-scale cases. The neighborhood structure operates the R&D and manufacturing parts of solution. Variable neighborhood descent with different amount and sequence of neighborhood structures is designed to enhance the effectiveness and efficiency of the proposed algorithm. Computational experiments are conducted to evaluate the performance of the proposed algorithm. The experimental results show that the proposed algorithm performs well in terms of the solution quality and running time.