Title :
Apply MGA to Multi-objective Flexible Job Shop Scheduling Problem
Author :
Yang, Xiaomei ; Zeng, Jianchao ; Liang, Jiye
Author_Institution :
Complex Syst. & Comput. Intell. Lab., Taiyuan Univ. of Sci. & Technol., Taiyuan, China
Abstract :
Through describing the characteristic of current genetic scheduling algorithm, a modified genetic scheduling algorithm (MGA) is proposed according to multi-objective Flexible Job Shop Scheduling Problem. This algorithm introduces a specific representation to reduce the solving space. It obtains the reasonable individuals by the selected principle and weakest link effect. Based on analyzing the benchmark of Flexible Job Shop Scheduling Problem, the computation results validate the effectivity of the proposed algorithm.
Keywords :
flexible manufacturing systems; genetic algorithms; job shop scheduling; genetic algorithm; modified genetic scheduling algorithm; multi-objective flexible job shop scheduling problem; Algorithm design and analysis; Competitive intelligence; Genetic algorithms; Industrial engineering; Information management; Innovation management; Intelligent systems; Job shop scheduling; Laboratories; Scheduling algorithm; Flexible Job Shop Scheduling Problem; Genetic Algorithm;
Conference_Titel :
Information Management, Innovation Management and Industrial Engineering, 2009 International Conference on
Print_ISBN :
978-0-7695-3876-1
DOI :
10.1109/ICIII.2009.414
