Galvanising lines consists of load/loading stations and a series of processing tanks that are generally energy-intensive. Each raw part needs to go through a number of processing stages sequentially. Job sizes and processing time vary from part to part, hence the need to derive an optimal schedule to minimise total processing time in a batch. The problem of minimizing the makespan on parallel processing machines using different scheduling algorithms is studied in this paper. A set of independent tasks were scheduled on parallel processors in order to minimize schedule length using Integer Linear Programming, Shortest Processing Time, Longest Processing Time, and Greedy Genetic algorithms. The experimental results demonstrated that our Greedy Genetic algorithm outperformed other algorithms on minimizing makespan on parallel processing machines.

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