Please use this identifier to cite or link to this item:
https://hdl.handle.net/10316/5482
Title: | MOTGA: A multiobjective Tchebycheff based genetic algorithm for the multidimensional knapsack problem | Authors: | Alves, Maria João Almeida, Marla |
Keywords: | Genetic algorithms; Multiple objective programming; Knapsack problem | Issue Date: | 2007 | Citation: | Computers & Operations Research. 34:11 (2007) 3458-3470 | Abstract: | This paper presents a new multiobjective genetic algorithm based on the Tchebycheff scalarizing function, which aims to generate a good approximation of the nondominated solution set of the multiobjective problem. The algorithm performs several stages, each one intended for searching potentially nondominated solutions in a different part of the Pareto front. Pre-defined weight vectors act as pivots to define the weighted-Tchebycheff scalarizing functions used in each stage. Therefore, each stage focuses the search on a specific region, leading to an iterative approximation of the entire nondominated set. | URI: | https://hdl.handle.net/10316/5482 | DOI: | 10.1016/j.cor.2006.02.008 | Rights: | openAccess |
Appears in Collections: | FEUC- Artigos em Revistas Internacionais |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
file05a6be401d2c47d590830409cb7cd42d.pdf | 373.56 kB | Adobe PDF | View/Open |
SCOPUSTM
Citations
52
checked on May 1, 2023
WEB OF SCIENCETM
Citations
50
42
checked on Oct 2, 2024
Page view(s)
369
checked on Oct 15, 2024
Download(s) 20
1,384
checked on Oct 15, 2024
Google ScholarTM
Check
Altmetric
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.