Genetic Algorithm Based Space-Optimised Arrangement of Containers and Stability in Containerships

Abstract

Abstract

Space optimization in a container terminal to prevent space wastage and ensure the stability of containers is an optimization problem frequently experienced at container terminals. Ineffective planning of the arrangement of containers creates the problem of stability, loading and unloading containers from one port to another, leading to time wastage. In this research, the optimization of containers stowage in containership is achieved by using genetic algorithm processes of selection, crossover, mutation, and fitness in order to determine the optimal arrangement of containers in container ships. The objective function, the solution representation, and the constraints were set, and a fitness function determines how good a candidate solution is. The algorithm is able to optimize space, thereby ensuring stability and preventing time wastage that comes with loading and unloading at different ports.

The experiment was conducted six times on the population size of one hundred 20-feet containers and one hundred 40-feet containers. The results show that an average percentage space utilization of 98.55% and an average time of 17.73 seconds were achieved. The algorithm is efficient for arranging any type and size of containers on containerships.