A new fuzzy knowledge-based optimisation system for management of container yard operations


Managing the container yard operations can be challenging as a result of various uncertainties associated with storing and retrieving containers from the yard. These associated uncertainties occur because the arrival of a truck to pick up the container is random, so the departure time of the container is unknown. The problem investigated in this paper emerges when newly arrived containers of different sizes, types and weights require storage operation in the same yard where other containers have already been stored. This situation becomes more challenging when the time of departure of existing container is not known. This study develops a new Fuzzy Knowledge-Based optimisation system named 'FKB_GA' for optimal storage and retrieval of containers in a yard that contains long stay pre-existing containers. The containers' duration of stay factor is considered along with two other factors such as the similarity (containers with same customer) and the quantity of containers per stack. A new Multi-Layered Genetic Algorithm module is proposed which identifies the optimal fuzzy rules required for each set of fired rules to achieve a minimum number of container re-handlings when selecting a stack. An industrial case study is used to demonstrate the applicability and practicability of the developed system.

Publication DOI: https://doi.org/10.1142/S0218213021500032
Divisions: College of Business and Social Sciences > Aston Business School
College of Business and Social Sciences > Aston Business School > Operations & Information Management
Additional Information: Publisher Copyright: © 2021 World Scientific Publishing Company.
Uncontrolled Keywords: 'ON/OFF' strategy,container yard operations,Fuzzy knowledge-based model,fuzzy rules,multi-layer genetic algorithm,Artificial Intelligence
Publication ISSN: 0218-2130
Full Text Link: https://core.ac ... d/334954694.pdf
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.wor ... 218213021500032 (Publisher URL)
PURE Output Type: Article
Published Date: 2021-03-26
Accepted Date: 2020-10-09
Authors: Al Bazi, Ammar (ORCID Profile 0000-0002-5057-4171)
Palade, Vasile
Abbas, Ali

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