Solving A Hybrid And Flexible Flow Shop Scheduling Problem With Time-Varying Demand For Fmcg Industry: A Case Of Unilever Vietnam

Abstract

In this research paper, we tackle the Hybrid Flowshop Scheduling Problem with Demand Variation (HFSP-DV), a challenging problem in production scheduling. We develop a mixed integer programming model tailored specifically for the HFSP-DV and propose a Genetic Algorithm (GA) approach to solve it. Through extensive computer tests on smallscale examples, we evaluate the performance of our proposed GA method and compare it with the benchmark solver CPLEX. We further apply the proposed GA method to a realworld case study of the HFSP-DV, validating its practical applicability. Our research contributes to scheduling optimization by addressing the HFSP-DV and providing effective approaches for managing demand variations, offering practical benefits for industries facing dynamic demand patterns.