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A Hybrid Genetic Algorithm for Solving Feeder Arrangement and Placement Sequencing Decisions in PCB Assembly

We consider the operation of a surface mounting technology (SMT) device that mounts various components provided by diverse types of feeders such as cassette, stick, and tray on a printed circuit board (PCB). The problem is to minimize the time needed to assemble a PCB using the SMT. We decompose the problem into two sub-problems, which are determining the allocation of component feeders and the mounting sequence of components, respectively. In this paper we propose a hybrid genetic approach to solve two sub-problems. Hybridization is achieved through constructing initial population by an ant colony optimization (ACO) procedure and improving an individual by a local search. Results from a computational experiment show that the proposed technique outperforms the conventional genetic heuristic procedures, providing good solutions more quickly.