A Novel Hybrid Algorithm for Minimizing Total Weighted Tardiness Cost

Abstract

In this research paper, we aim to present a hybrid algorithm in order to obtain a better solution to the single machine total weighted tardiness scheduling problem (SMTWT). Here, the proposed approach called guided genetic algorithm (GGA) is the combination of the standard genetic algorithm (GA), the Kangaroo technique (KA) and the weighted modified due date (WMDD) dispatching rule. The main idea of this hybridization is to take the advantages of the global search process assured by GA and the potent of the local search gained by KA during the evolution of the population initially improved by WMDD rule. Experimental results using a set of benchmark instances coming from OR-Library for different sizes showed its effectiveness compared with the classical genetic algorithm.

Keywords

• scheduling
• SMTWT
• genetic algorithm
• kangaroo algorithm
• WMDD rule
• OR-Library