Resource Allocation Strategy during COVID-19 Period and Linear Programming Model Based on Three Meta-Heuristic Algorithms

Abstract

English Teachers resource allocation problem (TRAP) which is a highly complex multi-level system is a talent scheduling problem (TSP) with limited human, material and financial resources. It is of great significance to study the allocation of teacher resource in a century-long plan based on education. In this paper, under the effective control of COVID-19, taking the Bayannur City of Inner Mongolia as an example, teaching sites are set up to study the TRAP for the resumption of classes in the graduating grade. In order to minimize the total cost of the whole distribution system, a multi-objective linear hybrid model (MOLHM) is proposed based on the fact about different demands on the number of teachers in each site, the different daily salary of teachers with different teaching experience and degree level, and the different cost of transporting teachers to respective destination. And three heuristic algorithms, ant colony optimization algorithm (ACOA), tabu search algorithm (TSA) and particle swarm optimization algorithm (PSOA) are used to solve the model. Through numerical experiments, the feasibility of them is verified, and the performances of them is compared in terms of optimization results and running time. In the system of the paper, the optimization result of ACOA is optimal, and TSA has better performance of running time. Under the condition that the equal number of ants and particles, the running time of PSOA is better than that of ACOA.