Scheduling is generally considered to be the one of the most significant issues in the
planning and operation of a manufacturing system. Better scheduling system has
significant impact on cost reduction, increased productivity, customer satisfaction and
overall competitive advantage. There are different systems of production scheduling
including flow shop in which jobs are to be processed through a series of machines for
optimizing a number of required performance measures. Scheduling seems to be an
intangible process which needs a thorough study to view it as a tangible process.
Scheduling problems in an industry contain a set of tasks to be carried out with a set of
limited resources available to perform these tasks. The general problem is to determine
the timing of the tasks while recognizing the capability of the resources with given
tasks and resources, together with some information about uncertainties. The present
industrial environment is characterized by markets facing competition from which
customer requirements and expectations are becoming increasingly high in terms of
quality, cost and delivery time. To achieve these goals, an organization needs implementation of a number of functions together with scheduling which plays a very
important role. The present paper discusses the optimization problem of scheduling
by using Genetic Algorithm (GA). Literature shows that very less work has been carried
out in this field by taking actual industrial data, which leads to unacceptable results
for an industry. Therefore, the present paper makes an attempt to bridge this gap by
carrying out an analysis using realistic data from a middle-scale ply board industry.
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