Evolutionary algorithm for optimization regarding the planning of topological facilities in layout of a shipyard
| Autor: | Walther Azzolini Junior, Frederico Gomes Pires Azzolini |
|---|---|
| Přispěvatelé: | Universidade de São Paulo (USP), Universidade Estadual Paulista (Unesp) |
| Jazyk: | Spanish; Castilian |
| Rok vydání: | 2019 |
| Předmět: |
Facilities Planning
0209 industrial biotechnology General Computer Science Computer science Topological Optimization Crossover Evolutionary algorithm Evolutionary Algorithm 020101 civil engineering 02 engineering and technology Genetic operator Grid Topology Expression (mathematics) 0201 civil engineering Reduction (complexity) Minimization of Materials Movement Cost 020901 industrial engineering & automation Position (vector) Biased Random-Key Genetic Algorithm Shipyard Genetic algorithm Electrical and Electronic Engineering |
| Zdroj: | Scopus Repositório Institucional da UNESP Universidade Estadual Paulista (UNESP) instacron:UNESP Web of Science |
| Popis: | Made available in DSpace on 2020-12-12T01:08:55Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-09-01 The purpose of this study is to contribute the approach to the problem of optimization regarding the planning of topological facilities in layout of a shipyard, with the objective of finding a robust solution to the problem by improving the solution space search through refining the genetic operators. For this, the computational results of the evolutionary algorithm proposed by Choi with changes made by the authors, being: 1) the use of the Partially-Matched Crossover (PMX) genetic operator; 2) the use of a recursive expression in the topological optimization step in addition to implementing the Biased Random-Key Genetic Algorithm (BRKGA) for the purpose of comparing the results. As a plan of the computational experiments two groups of experiments were performed: 1) with the parameters and variables of the work of Choi, in order to validate the efficiency and effectiveness of the AE proposed in this work and; 2) with the parameters and variables of the work of Choi with Department 03 fixed in the position of the best solution found in the 1st group of experiments (position 11 of the topological Grid). Each group contains 50 experiments with 100 iterations and variation of the number of individuals from 100 to 80,000 individuals. As a result, a better solution characterized by the reduction of material handling costs, of 11,816 presented by Choi, for 11,489 monetary units of cost, found from the changes made by the authors of the original proposal of the evolutionary algorithm and the use of BRKGA. University of São Paulo (USP) Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP) Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP) |
| Databáze: | OpenAIRE |
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