Estimation of distribution algorithm for the quay crane scheduling problem

Abstract

Estimation of Distribution Algorithms (EDA) are a type of optimization techniques that belong to evolutionary computation. Its operation is based on the use of a probabilistic model, which tries to reach promising regions through statistical information concerning to the individuals that belong to the population. In this work, several solution approaches based on the EDA field are presented in order to solve the Quay Crane Scheduling Problem (QCSP). QCSP consists of obtaining a schedule that minimizes the service time of a container vessel given a set of tasks (loading and unloading operations to/from) by means of the available quay cranes at a container terminal. The experimental results confirm that such algorithms are suitable for solving the QCSP and perform a wide exploration of the solution space using reduced computational times. © 2011 Springer-Verlag Berlin Heidelberg.