TY  - BOOK
AU  - Lacsamana, Margareth Ann Gallo
TI  - Modified shuffled frog-leaping algorithm (SFLA) applied to cutting stock problem
PY  - 2008///
KW  - Cutting stock problem
KW  - Combinatorial optimization
KW  - Optimization
KW  - Discrete optimization
KW  - Evolutionary algorithms
KW  - Genetic algorithm
KW  - Shuffled frog leaping algorithm
KW  - Uniform crossover
KW  - Undergraduate Thesis
KW  - CMSC200,
KW  - BSCS
N1  - Thesis (BS Computer Science) -- University of the Philippines Mindanao, 2008
N2  - This study focused on solving the one-dimensional variant of CSP with single stock length and without contiguity. In this study, an evolutionary algorithm (EA) called the shuffled frog-leaping algorithm (SFLA) was applied to the CSP. However, the local search of the SFLA was first modified using an operator from the genetic algorithm called the uniform crossover so s to use it in solving the CSP. The modified SFLA (MSLFA) with crossover was the only main algorithm used. The evaluation of the efficiency of the MSFLA was limited only to the chosen benchmark test problems. The experimental results in terms of the probability of convergence to a global optimal solution imply that the MSFLA can be an efficient tool for solving combinatorial optimization problems comparable to the EP. Generally, MSFLA provided equal results with EP in one of the benchmark test problems and an almost at par results with the EP in the other test problems with very little percentage error. Accordingly, MSFLA is a promising approach in solving the cutting stock problem if further improvements can be done
ER  -