Multi-objective optimization of cycle time and energy consumption in parallel robotic assembly lines using a discrete firefly algorithm

Abstract

Purpose: Assembly lines are one of the places where energy consumption is intensive in manufacturing enterprises. The use of robots in assembly lines not only increases productivity but also increases energy consumption and carbon emissions. The purpose of this paper is to minimize the cycle time and total energy consumption simultaneously in parallel robotic assembly lines (PRAL). Design/methodology/approach: Due to the NP-hardness of the problem, A Pareto hybrid discrete firefly algorithm based on probability attraction (PHDFA-PA) is developed. The algorithm parameters are optimized using the Taguchi method. To evaluate the results of the algorithm, a multi-objective programming model and a restarted simulated annealing (RSA) algorithm are used. Findings: According to the comparative study, the PHDFA-PA has a competitive performance with the RSA. Thus, it is possible to achieve a sustainable PRAL through the proposed method by addressing the cycle time and total energy consumption simultaneously. Originality/value: To the best knowledge of the authors, this is the first study addressing energy consumption in PRAL. The proposed method for PRAL is efficient in solving the multi-objective balancing problem.