A Constrained Fuzzy Knowledge-Based System for the Management of Container Yard Operations

Abstract

The management of container yard operations is considered by yard operators to be a very challenging task due to the many uncertainties inherent in such operations. The storage of the containers is one of those operations that require proper management for the efficient utilisation of the yard, requiring rapid retrieval time and a minimum number of re-handlings. The main challenge is when containers of a different size, type, or weight need to be stored in a yard that holds a number of pre-existing containers. This challenge becomes even more complex when the date and time for the departure of the containers are unknown, as is the case when the container is collected by a third-party logistics company without any prior notice being given. The aim of this study is to develop a new system for the management of container yard operations that takes into consideration a number of factors and constraints that occur in a real-life situation. One of these factors is the duration of stay for the topmost containers of each stack, when the containers are stored. Because the duration of stay for containers in a yard varies dynamically over time, an ‘ON/OFF’ strategy is proposed to activate/deactivate the duration of stay factor constraint if the length of stay for these containers varies significantly over time. A number of tools and techniques are utilised for developing the proposed system including: discrete event simulation for the modelling of container storage and retrieval operations, a fuzzy knowledge-based model for the stack allocation of containers, and a heuristic algorithm called ‘neighbourhood’ for the container retrieval operation. Results show that by adopting the proposed ‘ON/OFF’ strategy, 5% of the number of re-handlings, 2.5% of the total retrieval time, 6.6% of the total re-handling time and 42% of the average waiting time per truck are reduced.