scaled_single_worker_cost

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

Create a transition cost function for a problem where only a single worker can work on the transition between two consecutive runs. The total transition cost is determined by the sum of all transition costs. The transition cost is determined by scaling the transition cost between start and stop with a base cost. See the parameters for more information.

Parameters

transition_costsdict(str, tuple(float, float, float, float) or float)

A dictionary mapping the factor name to the transition cost. The cost is a tuple with as first element the base cost of any positive transition (-1 to +1), as second element the base cost of any negative transition (+1 to -1), as third element the additional cost to positively scale between min (-1) and max (+1), and as third element the additional cost to negatively scale between max (+1) and min (-1). Categorical factors should have only a float indicating the base cost of any transition.

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.