The findings on constructing a new approximation algorithm to solve the hospital’s scheduling model

Abstract

In reality, the scheduling model is an optimal model that many researchers are interested in due to its great complexity and high applicability in practice. Finding out the optimal solution in polynomial time is a big challenge, therefore scientists frequently study some near-optimal solutions implemented by approximation algorithms, typically greedy and evolutionary algorithms based on the mechanics of genetic algorithms. The main content of this paper is to present the research findings on approximation algorithms and genetic algorithms. On the basis of constructing and analyzing the scheduling model in the hospitals' clinics, this paper proposed approximation algorithms to solve this problem and conducted experiments on specific models to confirm the effectiveness of the proposed algorithms.