Robust Optimization Approach in Production Planning Problem Considering Rework, Backlogging and Breakdown under Conditions of Uncertainty: an Evolutionary Approach

Abstract

In this paper, we consider a multi-site production planning problem subject to uncertainty in demand and workforce expenses. In our new mathematical model, we presented a production planning system considering failure in rework and breakdown. We also survey human workforce allocation and its expenses which are considered uncertain due to some tradeoff between company's benefits and workforce union's advantages. We presented a new robust particle swarm optimization to propose a model with the ability of handling uncertainties. Firstly, we apply the presented robust optimization to handle demand uncertainty separately, and then we extended our model to regard both uncertainties simultaneously. To show the practicability of the proposed algorithm, we solved a real problem in an industrial case study. We also analyzed the most important parameters in the presented robust model to find out which level of uncertainty has less constraint violation and determine the maximum budget of uncertainties that could be considered in the proposed model to expect acceptable optimal objective. The results showed that the proposed model can prepare a promising approach to fulfill an efficient production planning in a multi-site production planning.