Studies on Microhabitat ACO for application to JSSP

Author

Yi, Gan ; Zhi-wei, Zhang ; Sheng, Li

Author_Institution

Coll. of Mech. Eng., Univ. of Shanghai for Sci. & Technol., Shanghai, China

Volume

3

fYear

2010

fDate

9-10 Jan. 2010

Firstpage

1851

Lastpage

1855

Abstract

Through parallel and diversified optimizing activities in ant colony, Microhabitat Ant Colony Optimization Stratagem (MACOS) was advanced to improve the basic ACO from diversity of pheromones distribution, ant pheromone update strategy and diversity of information exchange. Basic Scheduling Rules of Ants (BSRA)was built up based on the characteristics of JSSP. Ant Colony Optimization Scheduling Rules (MACO SR) were built up based on MACOS to solve JSSP and improve BSRA. And waiting time was integrated into the heuristic function and path updating of MACO SR. It proves that MACO SR can achieve more satisfactory results than basic ACO and BSRA for JSSP with the objects function of minimizes the makespan.

Keywords

job shop scheduling; optimisation; BSRA; JSSP; MACO SR; MACOS; ant colony optimization scheduling rules; ant pheromone update strategy; basic scheduling rules of ants; heuristic function; information exchange diversity; microhabitat ACO; microhabitat ant colony optimization stratagem; optimizing activity; path updating; pheromones distribution; Ant colony optimization; Ecosystems; Educational institutions; Feedback; Gallium nitride; Heuristic algorithms; Job shop scheduling; Parallel processing; Scheduling algorithm; Strontium; Job Shop Scheduling Problem; Microhabitat ant Colony Optimization; Scheduling Rules;

fLanguage

English

Publisher

ieee

Conference_Titel

Logistics Systems and Intelligent Management, 2010 International Conference on

Conference_Location

Harbin

Print_ISBN

978-1-4244-7331-1

Type

conf

DOI

10.1109/ICLSIM.2010.5461320

Filename

5461320