Clustering Nodes and Discretizing Movement to Increase the Effectiveness of HEFA for a CVRP

Abstract

A Capacitated Vehicle Routing Problem (CVRP) is an important problem in transportation and industry. It is challenging to be solved using some optimization algorithms. Unfortunately, it is not easy to achieve a global optimum solution. Hence, many researchers use a combination of two or more optimization algorithms, which based on swarm intelligence methods, to overcome the drawbacks of the single algorithm. In this research, a CVRP optimization model, which contains two main processes of clustering and optimization, based on a discrete hybrid evolutionary firefly algorithm (DHEFA), is proposed. Some evaluations on three CVRP cases show that DHEFA produces an averaged effectiveness of 91.74%, which is much more effective than the original FA that gives mean effectiveness of 87.95%. This result shows that clustering nodes into several clusters effectively reduces the problem space, and the DHEFA quickly searches the optimum solution in those partial spaces.

Provide A Method To Optimize the Reduction of Energy Consumption in Wireless Sensor Networks Using the Cuckoo Algorithm

“…Generally, this time is normalized by dividing by its maximum value so that the value is in the range [0, 1]. Hence the lifetime of the network is defined using the following relation [10,11] .…”