Abstract
A multi-stage Hybrid Flow Shop (HFS) scheduling is characterized ‘n’ jobs ‘m’ machines with ‘M’ stages in series with unidirectional flow of work with a variety of jobs being processed sequentially in a single-pass manner. Most real world scheduling problems are NP-hard in nature. The essential complexity of the problem necessitates the use of meta-heuristics for solving hybrid flow shop scheduling problem. The paper addresses multi-stage hybrid flow shop scheduling problems with missing operations to minimize the makespan time with the specific batch size using Genetic Algorithm (GA) and Simulated Annealing algorithm (SA). It is observed that the GA algorithm yields good quality solutions than SA with lesser computational time.
Published Version
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