Workforce Assignment in Assembly Line Considering Uncertain Demand

Abstract

In this work, we study a workforce assignment problem in the assembly line with several stations and executing some parts of different types. The objective is to minimize the number of workers over all the production line. Due to the complex business environment, changes in demand have great influence on production scheduling. Therefore, we consider uncertain demand in our investigated problem. To the best of our knowledge, we are the first to consider stochastic demand in assembly line problem with workers assigning. The main contributions include: 1) an ambiguity set is applied to portray the demand uncertainty, 2) a joint chance-constrained programming model is proposed, and 3) we choose two distribution-free approaches, namely Approximations based on Markov Inequality (AMI) and Mixed Integer Second-Order Conic Program (MI-SOCP), to approximate the chance constraints of the model. Finally, computational experiments are conducted to compare performances of the two methods.