moheftAlgorithm.process(maxRelAlgorithm.individual, max_rel)
moheft_result_sort_by_makespan = sort_result_by_makespan(moheftAlgorithm.pareto_result)
FileUtil.dump_result_to_file(moheft_result_sort_by_makespan, moheftAlgorithm.name, workflow.name,
percentage)
metric_result = list()
# Q-metric
evaluation = EvaluationMetric()
metric_result.append(evaluation.q_metric(randomAlgorithm.pareto_result, moheftAlgorithm.pareto_result))
metric_result.append(evaluation.q_metric(randomAlgorithm.pareto_result, mowsDtmAlgorithm.pareto_result))
metric_result.append(evaluation.q_metric(moheftAlgorithm.pareto_result, mowsDtmAlgorithm.pareto_result))
# FS-metric
metric_result.append(evaluation.fs_metric(randomAlgorithm.pareto_result))
metric_result.append(evaluation.fs_metric(moheftAlgorithm.pareto_result))
metric_result.append(evaluation.fs_metric(mowsDtmAlgorithm.pareto_result))
# S-metric
metric_result.append(evaluation.s_metric(randomAlgorithm.pareto_result))
metric_result.append(evaluation.s_metric(moheftAlgorithm.pareto_result))
metric_result.append(evaluation.s_metric(mowsDtmAlgorithm.pareto_result))
FileUtil.dump_metric_result_to_file(
metric_result,
"%s_%s_%s_%s_%s" % (
workflow.name, randomAlgorithm.name, mowsDtmAlgorithm.name, moheftAlgorithm.name, percentage)
)
# if len(mowsDtmAlgorithm.pareto_result) >= 10:
# break
evaluation = EvaluationMetric()
metric_result.append(
evaluation.q_metric(randomAlgorithm.pareto_result,
moheftAlgorithm.pareto_result))
metric_result.append(
evaluation.q_metric(randomAlgorithm.pareto_result,
mowsDtmAlgorithm.pareto_result))
metric_result.append(
evaluation.q_metric(moheftAlgorithm.pareto_result,
mowsDtmAlgorithm.pareto_result))
# FS-metric
metric_result.append(evaluation.fs_metric(randomAlgorithm.pareto_result))
metric_result.append(evaluation.fs_metric(mowsDtmAlgorithm.pareto_result))
metric_result.append(evaluation.fs_metric(moheftAlgorithm.pareto_result))
# S-metric
metric_result.append(evaluation.s_metric(randomAlgorithm.pareto_result))
metric_result.append(evaluation.s_metric(mowsDtmAlgorithm.pareto_result))
metric_result.append(evaluation.s_metric(moheftAlgorithm.pareto_result))
FileUtil.dump_metric_result_to_file(
metric_result, "%s_%s_%s" %
(randomAlgorithm.name, mowsDtmAlgorithm.name, moheftAlgorithm.name))
# for delta in [0, 1, 3, 5, 7]:
# mowsDtmAlgorithm = GeneticAlgorithm(workflow, bw_value, delta=delta)
# mowsDtmAlgorithm.process()
# mows_dtm_result_sort_by_makespan = sort_result_by_makespan(mowsDtmAlgorithm.pareto_result)
# FileUtil.dump_result_to_file(mows_dtm_result_sort_by_makespan, mowsDtmAlgorithm.name)
