Ant Colony Optimization for the Mixed-Model U-Shaped Assembly Line Balancing Problem
Date Issued
2009
Date
2009
Author(s)
Lai, Hao-De
Abstract
The mathematical model of the mixed-model U-shaped assembly line balancing problem is first rigorously defined in this thesis. This research proposes an Ant Colony Optimization (ACO) method for the tasks of line balancing and model sequencing involved in the problem. The pitfall and fitness for the objective functions using the minimum cycle time (CT) and the absolute deviation of workloads (ADW) are discussed. Two operation scenarios are simulated for the assembly line to determine the cycle times of all of the subcycles: (1) each task assigned to a workstation is processing on an individual model instance, and (2) successive tasks assigned to a workstation are processing on the same model instance. An ant platoon consisting of three squads with different heuristic value evaluations is proposed to guide the solution construction for line balancing. The first task for an ant is to construct a sequence of assembly tasks subject to the precedence constraints and create workstation one after the other to host the tasks. The second task is to construct a model sequence. Our method uses a solution set augmentation technique to enlarge the number of solutions and then adopts the segment-based pheromone update strategy from the segment discriminated ant system (SDAS). A software prototype system is developed to implement the proposed method. Several numerical tests are conducted on benchmarks to evaluate the performance of the proposed method. Numerical results show that the ADW objective function, compared with the one with CT, is unable to maximize the line efficiency. In addition, the proposed ACO method significantly outperforms the existing solving algorithms in solving the discussed problems.
Subjects
Assembly line balancing problem
Line balancing
Model sequencing
Mixed-model U-shaped line
Ant Colony Optimization
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-98-R96546029-1.pdf
Size
23.53 KB
Format
Adobe PDF
Checksum
(MD5):35f879bebbd2c3580757555295d44295