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2017 | OriginalPaper | Chapter

An Elitist Non-dominated Sorting Hybrid Evolutionary Algorithm for Multi-objective Constrained Ship Arrangements Optimization Problem

Authors : Hao Wang, Shunhuai Chen, Liang Luo

Published in: Bio-inspired Computing: Theories and Applications

Publisher: Springer Singapore

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Abstract

As the complexity of ship arrangements increases, general arrangements optimization technology based on evolutionary algorithms has emerged, giving enormous potential to assist designers in enhancing the range of alternative arrangements and in expediting the design process. This paper presents a hybrid evolutionary algorithm to handle the multi-objective constrained arrangements optimization problem based on elitist non-dominated sorting strategy. To enhance the efficiency of optimization, a hybrid evolutionary algorithm that couples an NSGA-II with a stochastic local search technique is used to find feasible solutions rapidly and facilitate local optimization. However, the algorithm that can rapidly find feasible solutions is also expected to contribute to better optimization. It has also been observed that lack of diversity of potential solutions leads to a local optimal solution which means the coherent arrangements could not be discovered. Hence, a modified replacement strategy is proposed to overcome this drawback. The final experimental results illustrate that the algorithm is capable of generating coherent arrangements.

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Metadata
Title
An Elitist Non-dominated Sorting Hybrid Evolutionary Algorithm for Multi-objective Constrained Ship Arrangements Optimization Problem
Authors
Hao Wang
Shunhuai Chen
Liang Luo
Copyright Year
2017
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-7179-9_5

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