Title :
Multi-stage order sequencing model and application of revised ACO algorithm in JIT manufacturing environment
Author :
Wang Xue-feng ; Chen Zhi-xiang
Author_Institution :
Sch. of Bus., Sun Yat-sen Univ., Guangzhou, China
Abstract :
Ant colony algorithm (ACA) is an intelligent optimization algorithm based on the behavior of ants seeking a shortest path between their colony and a source of food guided by their pheromone trails. Preliminary study indicates that it has superiority in solving complicated optimization problems. Order sequencing problem is a typical combinatorial optimization problem. This paper presents a model of order sequencing on multi-stage processing in JIT manufacturing environment and employs ACA to find the optimal solution for this model with detail algorithm steps. Testing the algorithm on experimental data, the paper validates its effectiveness on finding optimal solutions and its computational efficient as well.
Keywords :
combinatorial mathematics; just-in-time; order processing; JIT manufacturing environment; combinatorial optimization problem; intelligent optimization algorithm; multistage order sequencing model; revised ant colony optimization algorithm; Ant colony optimization; Computational intelligence; Costs; Delay effects; Food manufacturing; Job shop scheduling; Marketing and sales; Production facilities; Sun; Virtual manufacturing; JIT manufacturing; ant colony algorithm; order sequencing;
Conference_Titel :
Industrial Engineering and Engineering Management, 2009. IE&EM '09. 16th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-3671-2
Electronic_ISBN :
978-1-4244-3672-9
DOI :
10.1109/ICIEEM.2009.5344219