Eco-friendly multi-skilled worker assignment and assembly line balancing problem

Workforce assignment and energy consumption impact greatly on the manufacturing performance. In this work, we study a multi-skilled worker assignment and assembly line balancing problem with the consideration of energy consumption. The problem consists of scheduling products and assigning workers to workstations appropriately under a given cycle time. Two objectives are minimized simultaneously, i.e., (1) the total costs including the processing cost and the fixed cost induced by employing workers, and (2) the energy consumption. A bi-objective mixed-integer linear programming model is formulated and an epsilon-constraint method is adopted to obtain the Pareto front for small-scale problems. For solving large-size problems, a processing time and energy consumption sorted-first rule (PT-EC SFR), a multi-objective genetic algorithm (NSGA-II) and a multi-objective simulated annealing method (MOSA) are developed. Numerical experiments are conducted and computational results show that the designed PT-EC SFR outperforms the other two algorithms in terms of computational time and quality of solutions.

Automated summary

This study focuses on the multi-skilled worker assignment and assembly line balancing problem with the consideration of energy consumption. By utilizing a bi-objective optimization approach, a processing time and energy consumption sorted-first rule is developed, which outperforms other algorithms in terms of computational time and solution quality.