TITLE:
Heuristics for Mixed Model Assembly Line Balancing Problem with Sequencing
AUTHORS:
Panneerselvam Sivasankaran, Peer Mohamed Shahabudeen
KEYWORDS:
Assembly Line Balancing, Genetic Algorithm, Crossover Operation, Mixed-Model, Model Sequencing, Makespan
JOURNAL NAME:
Intelligent Information Management,
Vol.8 No.3,
May
31,
2016
ABSTRACT: The growing global competition compels
organizations to use many productivity improvement techniques. In this
direction, assembly line balancing helps an organization to design its assembly
line such that its balancing efficiency is maximized. If the organization
assembles more than one model in the same line, then the objective is to
maximize the average balancing efficiency of the models of the mixed model
assembly line balancing problem. Maximization of average balancing efficiency
of the models along with minimization of makespan of sequencing models forms a
multi-objective function. This is a realistic objective function which combines
the balancing efficiency and makespan. This assembly line balancing problem
with multi-objective comes under combinatorial category. Hence, development of
meta-heuristic is inevitable. In this paper, an attempt has been made to
develop three genetic algorithms for the mixed model assembly line balancing
problem such that the average balancing efficiency of the model is maximized
and the makespan of sequencing the models is minimized. Finally, these three
algorithms and another algorithm in literature modified to solve the
mixed-model assembly line balancing problem are compared in terms of the stated
multi-objective function using a randomly generated set of problems through a
complete factorial experiment.