Pareto clustering search applied for 3D container ... - BV FAPESP
Advanced search
Start date
Betweenand
(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Pareto clustering search applied for 3D container ship loading plan problem

Full text
Author(s):
Araujo, Eliseu Junio [1] ; Chaves, Antonio Augusto [1] ; de Salles Neto, Luiz Leduino [1] ; de Azevedo, Anibal Tavares [2]
Total Authors: 4
Affiliation:
[1] Univ Fed Sao Paulo, Sao Jose Dos Campos - Brazil
[2] Univ Estadual Campinas, Limeira - Brazil
Total Affiliations: 2
Document type: Journal article
Source: EXPERT SYSTEMS WITH APPLICATIONS; v. 44, p. 50-57, FEB 2016.
Web of Science Citations: 5
Abstract

The 3D Container ship Loading Plan Problem (CLPP) is an important problem that appears in seaport container terminal operations. This problem consists of determining how to organize the containers in a ship in order to minimize the number of movements necessary to load and unload the container ship and the instability of the ship in each port. The CLPP is well known to be NP-hard. In this paper, the hybrid method Pareto Clustering Search (PCS) is proposed to solve the CLPP and obtain a good approximation to the Pareto Front. The PCS aims to combine metaheuristics and local search heuristics, and the intensification is performed only in promising regions. Computational results considering instances available in the literature are presented to show that PCS provides better solutions for the CLPP than a mono-objective Simulated Annealing. (C) 2015 Elsevier Ltd. All rights reserved. (AU)

FAPESP's process: 12/17523-3 - New hybrid methods to resolve combinatorial optimization problems
Grantee:Antônio Augusto Chaves
Support Opportunities: Research Grants - Young Investigators Grants