Dileeplal, J; Dr.Narayanan, K P(Cochin University of Science And Technology, August , 2012)
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Abstract:
Assembly job shop scheduling problem (AJSP) is one of the most complicated
combinatorial optimization problem that involves simultaneously scheduling the
processing and assembly operations of complex structured products. The problem
becomes even more complicated if a combination of two or more optimization
criteria is considered. This thesis addresses an assembly job shop scheduling
problem with multiple objectives. The objectives considered are to simultaneously
minimizing makespan and total tardiness.
In this thesis, two approaches viz., weighted approach and Pareto approach are
used for solving the problem. However, it is quite difficult to achieve an optimal
solution to this problem with traditional optimization approaches owing to the
high computational complexity. Two metaheuristic techniques namely, genetic
algorithm and tabu search are investigated in this thesis for solving the multiobjective
assembly job shop scheduling problems.
Three algorithms based on the two metaheuristic techniques for weighted
approach and Pareto approach are proposed for the multi-objective assembly job
shop scheduling problem (MOAJSP). A new pairing mechanism is developed for
crossover operation in genetic algorithm which leads to improved solutions and
faster convergence.
The performances of the proposed algorithms are evaluated through a set of test
problems and the results are reported. The results reveal that the proposed
algorithms based on weighted approach are feasible and effective for solving
MOAJSP instances according to the weight assigned to each objective criterion
and the proposed algorithms based on Pareto approach are capable of producing a
number of good Pareto optimal scheduling plans for MOAJSP instances.
Description:
Department of Ship Technology, Cochin University of Science And Technology