parallel_worker_cost

pyoptex.doe.cost_optimal.cost.parallel_worker_cost(transition_costs, factors, max_cost, execution_cost=1)

Create a transition cost function for a problem where multiple workers can work on the transition between two consecutive runs in parallel. The total transition cost is determined by the most-hard-to-change factor.

Parameters

transition_costsdict(str, float)

A dictionary mapping the factor name to the transition cost.

factorslist(Factor)

The factors for the design.

max_costfloat

The budget available for this cost function.

execution_costfloat

the execution cost of a run.

Returns

cost_fnfunc(Y, params)

The cost function.