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Two-sided Assembly Line Balancing (2S-ALB) is important in assembly plants that produce large-sized high-volume products, such as in automotive production. The 2S-ALB problem involves different assembly resources such as worker skills, tools, and machines required for the assembly. This research modelled and optimised the 2S-ALB with resource constraints. In the end, besides having good workload balance, the number of resources can also be optimised. For optimisation purpose, Particle Swarm Optimisation was modified to reduce the dependencies on a single best solution. This was conducted by replacing the best solution with top three solutions in the reproduction process. Computational experiment result using 12 benchmark test problems indicated that the 2S-ALB with resource constraints model was able to reduce the number of resources in an assembly line. Furthermore, the proposed modified Particle Swarm Optimisation (MPSO) was capable of searching for minimum solutions in 11 out of 12 test problems. The good performance of MPSO was attributed to its ability to maintain the particle diversity over the iteration. The proposed 2S-ALB model and MPSO algorithm were later validated using industrial case study. This research has a twofold contribution; novel 2S-ALB with resource constraints model and also modified PSO algorithm with enhanced performance.

Optimisation of Two-sided Assembly Line Balancing with Resource Constraints Using Modified Particle Swarm Optimisation