Combining meta-heuristics to effectively solve the vehicle routing problems with time windows

The vehicle routing problems with time windows are challenging delivery problems in which instances involving 100 customers or more can be difficult to solve. There were many interesting heuristics proposed to handle these problems effectively. In this paper, we examined two well-known meta-heuristics and carefully combined the short-term and long-term memory-like mechanisms of both methods to achieve better results. Our prototype was shown to compare favorably against the original search methods and other related search hybrids on the Solomon's test cases. More importantly, our proposal of integration opens up many exciting directions for further investigation.