Heuristics for multiobjective optimization of two-sided assembly line systems.
Products such as cars, trucks, and heavy machinery are assembled by two-sided assembly line. Assembly line balancing has significant impacts on the performance and productivity of flow line manufacturing systems and is an active research area for several decades. This paper addresses the line balancing problem of a two-sided assembly line in which the tasks are to be assigned at L side or R side or any one side (addressed as E). Two objectives, minimum number of workstations and minimum unbalance time among workstations, have been considered for balancing the assembly line. There are two approaches to solve multiobjective optimization problem: first approach combines all the objectives into a single composite function or moves all but one objective to the constraint set; second approach determines the Pareto optimal solution set. This paper proposes two heuristics to evolve optimal Pareto front for the TALBP under consideration: Enumerative Heuristic Algorithm (EHA) to handle problems of small and medium size and Simulated Annealing Algorithm (SAA) for large-sized problems. The proposed approaches are illustrated with example problems and their performances are compared with a set of test problems.
Department of Mechanical Engineering, Thiagarajar College of Engineering, Madurai, Tamilnadu 625 015, India.
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Jawahar
Advanced Engineering Platform and School of Engineering, Monash University Malaysia, 46150 Bandar Sunway, Malaysia.
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Ponnambalam
Department of Mechanical Engineering, Thiagarajar College of Engineering, Madurai, Tamilnadu 625 015, India.
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Sivakumar
Department of Manufacturing Engineering, Central Institute of Plastics Engineering & Technology, (Government of India), Chennai, Tamilnadu 600 032, India.
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Thangadurai
D000465:Algorithms; D001185:Artificial Intelligence; D004526:Efficiency; D008962:Models, Theoretical