A novel line balancing problem: Complex constrained assembly line balancing

The primary aim of this dissertation is to extend the rule-based assembly modeling and to introduce a novel assembly line balancing problem: complex-constrained assembly line balancing problem (CCALBP), which is of the general ALBPs, in order to model all assembly constraints through a rule-base to tackle alternative ways of assembling a product and their effects on task times, precedence relations and the line balance simultaneously.A genetic algorithm (GA) based on the rule-base is proposed and discussed in detail to solve CCALBP. The specific characteristics of the proposed GA are explained on an example problem. The control parameters of the GA are optimized to improve the performance. Since CCALBP is a novel problem, there is no set of benchmark instances for testing. Therefore, the computational experiments are carried out on a set of self-made instances generated by adapting well-known benchmark problems from the literature. Some alternative routes are created and added to these literature problems. Based on the experiments, the proposed GA is proven to perform better. It is shown that line balancing improves when more alternatives are added to CCALBP.It is also shown how to map a rule-based assembly model to a constraint programming (CP) model and an integer programming (IP) model. CCALBP can be solved only through rule-based modeling, but not graph-based modeling. The efficiency and modeling capability of CP and IP models are discussed, and compared with that of traditional precedence graphs.