An ANFIS-based dispatching rule for complex fuzzy job shop scheduling problem

Author

Dong, Mingyu ; Liu, Min

Author_Institution

Siemens Ltd., China

fYear

2011

fDate

26-28 March 2011

Firstpage

263

Lastpage

266

Abstract

Complex job shop scheduling problems are mostly NP-hard. When some knowledge is imprecise, e.g., the processing times are denoted by fuzzy numbers, the fuzzy scheduling problems need new methods to be handled. ANFIS has some characteristics of self- learning, the nonlinear mapping and the form of if-then fuzzy rules. So this paper adopts ANFIS to combine the heuristic rules nonlinearly and takes the ANFIS as an adaptive scheduling rule to sort jobs. This is the first attempt to apply ANFIS in fuzzy job shop scheduling problems with parallel machines. The simulation tests show the feasibility of this method and it performs better than the heuristic rules.

Keywords

adaptive scheduling; fuzzy reasoning; fuzzy set theory; job shop scheduling; optimisation; parallel machines; ANFIS; NP-hard problem; adaptive neuro fuzzy inference system; adaptive scheduling rule; complex fuzzy job shop scheduling; dispatching rule; fuzzy number; heuristic rule; if-then fuzzy rule; nonlinear mapping; parallel machine; selflearning; Adaptive systems; Dispatching; Job shop scheduling; Optimal scheduling; Parallel machines; Pragmatics; Schedules;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Science and Technology (ICIST), 2011 International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4244-9440-8

Type

conf

DOI

10.1109/ICIST.2011.5765250

Filename

5765250