Name
Title | ||
|---|---|---|
An Effective Fruit Fly Optimization Algorithm For The Hybrid Flowshop Scheduling Problem |
Abstract | ||
|---|---|---|
Fruit Fly algorithm (FFO) is a recently reported meta-heuristics originally designed for function optimization problems. This paper proposes an effective FFO to solve the hybrid flowshop scheduling (HFS) problem with the aim of makespan optimization (minimization). In presented FFO, we utilize the permutation-based representation and operators. The presented FFO can directly explore the discrete solution space of the HFS problem. Extensive comparisons are carried out with well-known meta-heuristics. The results show that the developed FFO is very effective for the considered HFS problem. |
Year | Venue | Keywords |
|---|---|---|
2017 | 2017 13TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD) | evolutionary algorithm, fruit fly optimization, hybrid flowshop, makespan |
Field | DocType | Citations |
Mathematical optimization,Job shop scheduling,Computer science,Scheduling (computing),Permutation,Function optimization,Minification,Operator (computer programming),Optimization algorithm,Metaheuristic | Conference | 1 |
PageRank | References | Authors |
0.35 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jun-Hua Duan | 1 | 65 | 3.96 |
| Tao Meng | 2 | 39 | 2.52 |
| Quan-ke Pan | 3 | 222 | 22.89 |
| Qing-da Chen | 4 | 12 | 3.16 |