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Scheduling of jobs in Flow Shop (FS) is NP-hard problem which is usually solved by using heuristic and metaheuristic algorithms. In this paper modified Genetic Algorithm (GA) was used to solve FS scheduling problem to minimize the makespan. The proposed algorithm involved two improvements in GA. First is the modification in Roulette Wheel Selection (RWS) which is commonly used as a selection operator in GA. Secondly, the initialization of the population was created using NEH heuristic instead of random generation. The objective of these improvements in GA is to make smooth and fast convergence towards the best solution. A case study was conducted to evaluate the proposed algorithm using simulation. Experimental results demonstrated that the proposed algorithm can achieve a better solution with faster convergence as compared to GA with traditional RWS.
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