Title :
ALBO: An Assembly Line Balance Optimization Model Using Ant Colony Optimization
Author :
Lai, Lucas K C ; Liu, James N K
Author_Institution :
Dept. of Comput., Hong Kong Polytech. Univ., Hong Kong, China
Abstract :
In this paper an assembly line balance optimization model (ALBO) is proposed to solve the assembly line balance problem (ALB). It is a typical combinational optimization problem where pieces of work are transported between the work stations. In the ALB problem, the ultimate goal is to seek the optimal make span. ALB is currently dependent on human experts. We employed an evolutionary algorithm based on ant colony optimization technique. The efficiency records of three handbag styles having been running in the production lines for 2 months are used to test the ALBO model. It shows that the model can increase the efficiency by almost 13.88%. This is a great improvement as the efficiency of the actual production process is on average 15% below the current standard which could means millions of dollar in profitability.
Keywords :
assembling; combinatorial mathematics; evolutionary computation; optimisation; ant colony optimization; assembly line balance optimization model; combinational optimization problem; evolutionary algorithm; handbag styles; production process; Animals; Ant colony optimization; Artificial intelligence; Assembly; Evolutionary computation; Humans; Job shop scheduling; Production; Testing; Traveling salesman problems; Ant Colony Optimization; efficiency and Assembly Line Balance;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.693