Multi-objective Particle Swarm Optimisation for Cargo Packaging in Large Containers

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Abstract

Cargo management in all mode of transports like airlines, ships and trucks is a challenging task. The way in which an optimal allocation of packages in different containers are done using a software controlled method. An agent based software module is enabled as a service for the optimum allocation of cargo packages in the container terminals. There are multiple factors that will affect this allocation - size, shape, weight of the cargo packets and the container. When we design an optimal allocation module in a software these components need to be addressed along with capacity of the container. Hence, a multi-objective optimization algorithm will improve the performance of cargo management software. In this paper we suggest a Mixed Species Particle Swarm Optimisation (MSPSO) procedure for optimal allocation of cargo packages in containers of different size and capacity. The redesigned version of cargo management software performs well with search space on normal time complexity. The simulated results gives an improved optimised allocation than normalised allocation of cargo packets. The improved implementation performed better in terms of efficient cargo package allocation.

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APA

S S, V. C., Anand Hareendran, S., & S, S. S. (2020). Multi-objective Particle Swarm Optimisation for Cargo Packaging in Large Containers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12145 LNCS, pp. 415–422). Springer. https://doi.org/10.1007/978-3-030-53956-6_37

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