This paper considers the problem of scheduling a set of jobs on both a single machine and identical parallel machines settings with the objective of minimising the maximum completion time of all jobs (makespan). Jobs are subject to release dates and there are sequence-dependent setup times. Since this problem is known to be strongly NP-hard even for the single machine case, this paper proposes heuristic algorithms to solve it. Algorithm uses the advantages of random-variate generators as a strategy for the generation of various execution sequences, and then selects the best of such schedules. Experiments are performed using random-generated data from taken literature. Results show that the heuristics perform very well compared against the optimal solution, and requiring short computational time.