Application of Evolutionary Computation for Berth Scheduling at Marine Container Terminals: Parameter Tuning Versus Parameter Control

Abstract

Considering a substantial increase in the international seaborne containerized trade volumes, marine container terminal operators have to improve efficiency of the processes inside their terminals in order to meet the growing demand. An efficient berth scheduling is of a high importance for the terminal’s performance, as it significantly influences the turnaround time of vessels. This paper proposes a novel Evolutionary Algorithm to assist with berth scheduling at marine container terminals that, unlike published to date studies on berth scheduling, applies a parameter control strategy. Specifically, an adaptive mechanism is developed for the mutation operator, in which the mutation rate is altered based on feedback from the search. The objective of the proposed mixed integer model aims to minimize the total weighted vessel service cost. A set of numerical experiments are conducted to assess performance of the developed algorithm based on a comparison against a typical Evolutionary Algorithm that applies a constant mutation rate value, determined from the parameter tuning analysis. Results indicate that the optimality gap does not exceed 0.80% for both algorithms. Furthermore, deployment of the adaptive mechanism for the mutation operator yields an average of 5.4% and 8.5% savings in terms of the total weighted vessel service cost for medium and large size problem instances, respectively, without a significant increase in the computational time.