Research Article
A Novel Memetic Algorithm Based on Decomposition for Multiobjective Flexible Job Shop Scheduling Problem
Table 9
Comparison between MOMAD and other algorithms using C metric for Kacem and BR data instances.
| | Instance | MOMAD(A) versus MOGA(B) | MOMAD(A) versus PLS(C) | MOMAD(A) versus HSFLA(D) | MOMAD(A) versus HMOEA(E) | | | | | | | | |
| | ka | | | | | — | — | | | | ka | | | | | | | | | | ka | — | — | | | — | — | | | | ka | | 0.0000 | | | | | | | | ka | | 0.0000 | | | | | | | | MK01 | | 0.0000 | | 0.0000 | | 0.0000 | | 0.0000 | | MK02 | | 0.0000 | | 0.0000 | | 0.0000 | | 0.0000 | | MK03 | | 0.0000 | | 0.0000 | | 0.0000 | | | | MK04 | | 0.1034 | — | — | | 0.1724 | — | — | | MK05 | | | — | — | | 0.0000 | — | — | | MK06 | | 0.1387 | — | — | | 0.0438 | — | — | | MK07 | 0.0000 | | — | — | | 0.0000 | — | — | | MK08 | 0.0000 | | | 0.0000 | | 0.0000 | | | | MK09 | | 0.0000 | — | — | | 0.0000 | — | — | | MK10 | | 0.0000 | — | — | | 0.1747 | — | — |
|
|
For each instance, the greater set coverage values obtained by the compared algorithms are marked in bold.
|
