Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: S S, Vinod Chandra, Anand Hareendran, S., S, Saju Sankar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7354818/
http://dx.doi.org/10.1007/978-3-030-53956-6_37
_version_ 1783558171641511936
author S S, Vinod Chandra
Anand Hareendran, S.
S, Saju Sankar
author_facet S S, Vinod Chandra
Anand Hareendran, S.
S, Saju Sankar
author_sort S S, Vinod Chandra
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7354818
institution National Center for Biotechnology Information
language English
publishDate 2020
record_format MEDLINE/PubMed
spelling pubmed-73548182020-07-13 Multi-objective Particle Swarm Optimisation for Cargo Packaging in Large Containers S S, Vinod Chandra Anand Hareendran, S. S, Saju Sankar Advances in Swarm Intelligence Article 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. 2020-06-22 /pmc/articles/PMC7354818/ http://dx.doi.org/10.1007/978-3-030-53956-6_37 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
S S, Vinod Chandra
Anand Hareendran, S.
S, Saju Sankar
Multi-objective Particle Swarm Optimisation for Cargo Packaging in Large Containers
title Multi-objective Particle Swarm Optimisation for Cargo Packaging in Large Containers
title_full Multi-objective Particle Swarm Optimisation for Cargo Packaging in Large Containers
title_fullStr Multi-objective Particle Swarm Optimisation for Cargo Packaging in Large Containers
title_full_unstemmed Multi-objective Particle Swarm Optimisation for Cargo Packaging in Large Containers
title_short Multi-objective Particle Swarm Optimisation for Cargo Packaging in Large Containers
title_sort multi-objective particle swarm optimisation for cargo packaging in large containers
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7354818/
http://dx.doi.org/10.1007/978-3-030-53956-6_37
work_keys_str_mv AT ssvinodchandra multiobjectiveparticleswarmoptimisationforcargopackaginginlargecontainers
AT anandhareendrans multiobjectiveparticleswarmoptimisationforcargopackaginginlargecontainers
AT ssajusankar multiobjectiveparticleswarmoptimisationforcargopackaginginlargecontainers