A method based on SNSO for solving slot planning problem of container vessel bays

Abstract

Stowage planning has an important effect in container shipping and is also a hard combinatorial problem. In order to improve the operation efficiency and reduce the cost, a new optimization method called Social Network-based Swarm Optimization Algorithm (SNSO) is applied to solve the slot planning problem of container vessel bays. As a swarm intelligence optimization algorithm, SNSO is designed with considering population topology, neighborhood and individual behavior comprehensively to improve the swarm search ability. An effective coding and decoding strategy is proposed to optimize the slot planning problem for using SNSO. Finally, fourteen cases of slot planning with different scales are selected to test the proposed algorithm and five swarm intelligence algorithms are selected for comparison in the experiment. The results show that the SNSO has a better performance on solving stowage plan problem in the terms of convergence and accuracy than other selected algorithms.