Intelligent product mix and material match in electronics manufacturing.

Genetic Algorithms (GA) are innovative search algorithms based on natural phenomena whose main advantages lie in solving mostly high complex problems. This paper provides how a conventional GA can effectively solve the Product Mix and Material Match problem. Some novel ideas in chromosome representation and evaluation are also addressed. This GA approach produces good results with fast convergence speed at the shop floor level, which is verified and validated via real world applications. The product mix and material match approach may help the manager to control the production of electronics manufacturing to meet the customer's demand.