multi-objective two-sided robotic mixed-model assembly line balancing problem considering energy consumption and smoothing workload

In this paper, a type ii robotic mixed-model two-sided assembly line balancing problem is considered. this paper presents a new mixed-integer programming model for type ii robotic mixed-model two-sided assembly line balancing to minimize the cycle time, energy consumption, and purchased cost of robots for a given number of workstations. we provided an effective framework for optimizing the multi-objective robotic mixed-model two-sided assembly line balancing problem considering energy consumption and smoothing workload in the make to order environment to help the decision-makers make the right decisions under stochastic demand. an augmented epsilon constraint and lp-metric methods were applied to solve the problem, and then, with the help of defining two vertical and horizontal criteria, we attempt to help the decision-maker to choose a more efficient solution to make the production line more smooth workload. we demonstrate the efficiency of the proposed method by designing the numerical experiments.