Constraint programming models for parallel robotic assembly line balancing problems considering energy-efficiency

Several parallel assembly lines are balanced simultaneously in the parallel assembly line balancing problem (PALBP), which lead to several advantages such as increased capacity and flexibility against the changes in demand. Recently, the parallel robotic assembly line balancing problem (PRALBP) has emerged in the literature, due to the increase in automation of assembly lines. Robotic assembly lines have a significant potential to improve the consistency, efficiency and quality of the assembly processes. In this study, novel constraint programming (CP) models are presented for the PALBP and PRALBP. Comprehensive computational experiments by comparisons with the state-of-the-art algorithms show that the proposed CP models can achieve effective solutions for the PALBP and PRALBP in a short computational time. Particularly, the developed CP model improves the current best-known results for most of the benchmark instances for the PRALBP. Even though the PALBP has been extensively studied in the literature with the productivity-related objectives, the studies on PRALBP regarding the energy-efficiency have been very limited. Therefore, an energy-efficient PRALBP (E-PRALBP) is also addressed in this study, considering both cycle time-oriented and energy consumption-oriented variants of the problem. As an extension of the E-PRALBP, E-PRALBP with zoning constraints and limited number of robots (E-PRALBP-Z) is also considered. Consequently, this study presents novel CP models for the E-PRALBP and E-PRALBP-Z for the first time in the literature. A comprehensive computational study show that the proposed CP models can solve the E-PRALBP and E-PRALBP-Z effectively.