Research Information System
NEURAL COMPUTING & APPLICATIONS, no.11, pp.3183-3195, 2017 (SCI-Expanded)
This paper investigates the combined impact of assembly line balancing decisions within a supply chain network design. The aim of the problem is to design a supply chain network between manufacturers, assemblers, and customers for specific periods, as well as balancing the assembly lines in assemblers. The main objective is to minimize the sum of transportation costs and fixed costs of stations in assemblers. Solving this problem poses several methodological challenges. To this end, the paper developed a powerful evolutionary algorithm (EA) which was successfully applied to a large pool of benchmark instances. The EA solved instances with up to 140 manufacturers and customers, and with up to 130 assemblers. Computational analyses are performed to empirically calculate the effect of various problem parameters, such as total cost, transportation cost and number of stations. The EA is validated on benchmark instances where it provides competitive solutions. Several managerial insights are also presented.