Article Title
Performance Comparison of New Heuristic With Genetic Algorithm in Parallel Flow Line Set Up
Abstract
A new heuristic has been developed to solve the problem in parallel flow line scheduling. It involves the minimization of the makespan by the optimal allocation of a finite number of jobs to finite number of lines in the first phase and the optimal sequencing of allocated jobs in each line in the second phase. Here new heuristic and genetic algorithm for analyzing the parallel flow line scheduling are discussed and executed on a set of randomly generated problems. The results obtained for the test problems suggest that the developed new heuristic can be used successfully to solve large scale parallel flow line scheduling problems.
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