Mathematical model and metaheuristics for simultaneous balancing and sequencing of a robotic mixed-model assembly line. Issue 5 (4th May 2018)

• Record Type: Journal Article
• Authors: Li, Zixiang; Janardhanan, Mukund Nilakantan; Tang, Qiuhua; Nielsen, Peter
• Is Part Of: Engineering optimization. Volume 50:Issue 5(2018)
• Page Start: 877
• Page End: 893
• Publication Date: 2018-05-04
• Subjects: Assembly line balancing -- model sequencing -- robotic assembly line -- simulated annealing -- co-evolutionary algorithm; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2017.1351963
• Languages: English
• ISSNs: 0305-215X

Abstract

ABSTRACT: This article presents the first method to simultaneously balance and sequence robotic mixed-model assembly lines (RMALB/S), which involves three sub-problems: task assignment, model sequencing and robot allocation. A new mixed-integer programming model is developed to minimize makespan and, using CPLEX solver, small-size problems are solved for optimality. Two metaheuristics, the restarted simulated annealing algorithm and co-evolutionary algorithm, are developed and improved to address this NP-hard problem. The restarted simulated annealing method replaces the current temperature with a new temperature to restart the search process. The co-evolutionary method uses a restart mechanism to generate a new population by modifying several vectors simultaneously. The proposed algorithms are tested on a set of benchmark problems and compared with five other high-performing metaheuristics. The proposed algorithms outperform their original editions and the benchmarked methods. The proposed algorithms are able to solve the balancing and sequencing problem of a robotic mixed-model assembly line effectively and efficiently.