Modelling and optimization of assembly line balancing with multi-resource constraints

This research aim to model and optimize the assembly line balancing (ALB) with resource constraints. In different with existing work that assume all workstations have similar capability, this research consider the tool, worker and equipment constraints in the assembly process. Three ALB versions have been considered; the simple assembly line problem (SALB), two-sided assembly line problem (2S-ALB) and mixed-model assembly line problem (MMALB). All three version of ALB problems have been modelled to include the general resource constraints. The optimization was conducted by using different optimization algorithms. In SALB, we found that the Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II) have better performance. Meanwhile, for 2S-ALB and MMALB, the Particle Swarm Optimization and Ant colony Optimization have superior performance respectively. The validation for the problem ALB with resource constraints have been conducted in electronic and automotive assembly plant. The final result indicated that the proposed model is capable to improve the assembly efficiency and also capable to reduce the number of the resources required in assembly plant