42 lines
989 B
Python
42 lines
989 B
Python
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"""
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Input: Start and finish time of n jobs
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Output: Schedule with maximum number of non overlapping jobs
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The Strategy: At each step choose the job with earliest finish time
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Algorithm Type: Greedy
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Time Complexity: O(n*log(n))
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"""
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jobs = [
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(0, 2, 8), # (job_id, start_time, finish_time)
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(1, 6, 10),
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(2, 1, 3),
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(3, 4, 7),
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(4, 3, 6),
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(5, 1, 2),
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(6, 8, 10),
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(7, 10, 15),
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(8, 12, 16),
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(9, 14, 16)
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]
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def get_opt_schedule(jobs):
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"""
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Return the job_id's in the optimal jobs
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https://en.wikipedia.org/wiki/Interval_scheduling#Greedy_polynomial_solution
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>>> get_opt_schedule(jobs)
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[5, 4, 1, 7]
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"""
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opt_schedule = []
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sorted_jobs = sorted(jobs, key=lambda j: j[2])
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number_of_jobs = len(sorted_jobs)
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opt_schedule.append(sorted_jobs[0][0])
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for i in range(1, number_of_jobs):
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if sorted_jobs[i][1] >= jobs[opt_schedule[-1]][2]:
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opt_schedule.append(sorted_jobs[i][0])
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return opt_schedule
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if __name__ == "__main__":
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print(get_opt_schedule(jobs))
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