Bird mating optimizer for discrete berth allocation problem

Abstract

In this study, we apply Bird Mating Optimizer (BMO) algorithm for solving Berth Allocation Problem (BAP). The BMO is a nature-inspired optimization algorithm that imitates the mating behavior of bird species to breed broods with better genes in order to formulate superior searching techniques. BMO has more capability to effectively explore and exploit the search space and find the global solution by employing three operators to generate a new solution: two parent mating, multi-parents mating, and mutation. The BAP is a non-polynomial hard combinatorial optimization problem, which seeks to serve the vessels at discrete berth position and minimize the total handling and waiting time for all vessels. The performance of the proposed BMO is evaluated across benchmark instances with different sizes from the scientific literature. Experimental results demonstrate that the performance of the proposed BMO is comparable with the other methods in the literature for some instances. Indeed, the proposed BMO yields better results than CIPLEX algorithm on most instances. This demonstrated that the BMO is a promising optimization algorithm for solving berth allocation problem. Berth allocation problem (BAP); Bird mating optimizer (BMO); Contaier terminal (CT).