A robust optimization model for the wire bonding scheduling problem

This article considers the scheduling problem of wire bonding machine in a semiconductor assembly factory. There are unrelated parallel machines, and the decision maker is to determine the order of jobs under the environment of uncertain ready time, machine eligibility and sequence-dependent setup times. The objective is to minimize the weighted sum of setup time and delay time. A robust optimization model is proposed to obtain a close to optimal solution and satisfy all possible realizations of the uncertain data simultaneously. To solve the problem, a genetic algorithm embedded with neighborhood search operators has been developed. The chromosome has encoded with a feasibility function to penalize the violation of the constraints for certain realizations. Computational experiment shows that our method is outperformed in terms of solution quality and runtime.