Integrating Assembly Line Balancing in Product Family Planning Design under the Multinomial Logit Choice Model

Abstract

Product family planning (PFP) design considering its assembly line balancing (ALB) optimization has been well recognized by some scholars from the perspective of concurrent engineering. However, existing models for integrating ALB into PFP either have not accounted for the influence of customer purchase behaviors, or have focused on the deterministic choice model, in which each consumer will select the product that provides his or her maximum utility surplus. This paper formulates a nonlinear optimization model with the objective of maximizing the total profit for the joint decision-making of PFP and ALB under the multinomial logit (MNL) choice model. A modified genetic algorithm is developed for solving the optimization model. A case study of office chair product family is presented to illustrate the feasibility and potential of the proposed model and algorithm. The results indicate that the total profit derived from PFP and ALB will be underestimated under the traditional sequential approach, and it will be overestimated under the deterministic choice model. Sensitivity analysis is also made for the parameters of the model under the MNL choice model, and the corresponding managerial insights are provided.