MoneyMaker Hip Pump cost minimization problem

A citation-backed nonlinear optimization benchmark that fixes a target flow and tank head, then minimizes projected pump cost using a scalarized form of the MoneyMaker Hip Pump studies.

See Optimization Problem Catalog for the optimization family index.

Quick Facts

Field	Value
Problem ID	`moneymaker_hip_pump_cost_min`
Problem Family	optimization
Implementation	`design_research_problems.problems.optimization._moneymaker:MoneyMakerHipPumpProblem`
Capabilities	`baseline-solver`, `bounded-variables`, `citation-backed`, `equality-constraint`, `statement-markdown`
Study Suitability	none
Tags	`optimization`, `continuous`, `nonlinear`, `hydraulic`, `scalarized`, `moneymaker`

Taxonomy

Formulation: nonlinear_program
Convexity: not_guaranteed
Design Variable Type: continuous
Is Dynamic: no
Orientation: engineering-practical
Feasibility Ratio Hint: 0.1
Objective Mode: single
Constraint Nature: hard
Bounds Summary: 10 reduced continuous variables with fixed 3 m delivery head and reconstructed geometry relationships
Tags: optimization, continuous, nonlinear, hydraulic, scalarized, moneymaker

Statement

This packaged optimization problem is a scalarized subproblem derived from the published multi-objective MoneyMaker Hip Pump studies. It uses the epsilon-constraint pattern from the papers: the delivery head is fixed at 3 m, the target flow rate is fixed at 0.18 L/s, and the scalar objective is the projected pump cost.

To fit the current single-objective API cleanly, the packaged instance reduces the original 16 design variables to 10 independent continuous variables. The remaining geometric relationships and fixed deployment assumptions are reconstructed internally from the cited formulation. Bounds are centered on the published tall-tank designs so the packaged benchmark stays well-conditioned without changing the shared optimization base classes.

Problem Shape

Field	Value
Design Variable Count	10
Bound Summary	10 reduced continuous variables with fixed 3 m delivery head and reconstructed geometry relationships
Total Constraint Count	10
Equality Constraint Count	3
Inequality Constraint Count	7

Variable Bounds

Variable	Lower Bound	Upper Bound
`x[0]`	0.014	0.028
`x[1]`	0.038	0.05
`x[2]`	0.5	0.7
`x[3]`	0	18
`x[4]`	0.5	0.75
`x[5]`	0.014	0.024
`x[6]`	40	150
`x[7]`	110	140
`x[8]`	0.15	0.6
`x[9]`	0.2	0.3

Manifest Parameters

Key	Value
horizontal_run_m	18
target_flow_rate_lps	0.18
target_tank_height_m	3
well_depth_m	7

Library Interface

generate_initial_solution(seed=None)
objective(x)
evaluate(x)
solve(initial_solution=None, seed=None, maxiter=200)

Sources

Key	Summary
`mccomb2018moneymaker`	McComb et al. (2018).
`mccomb2014moneymaker`	McComb et al. (2014).

Raw Citation Records

McComb, C., Johnson, N. G., Santaeufemia, P. S., Gorman, B. T., Kolste, B., Mobley, A., and Shimada, K. (2018). Multi-objective optimization and scenario-based robustness analysis of the MoneyMaker Hip Pump. Development Engineering, 3, 23-33.

McComb, C., Santaeufemia, P. S., Johnson, N. G., and Shimada, K. (2014). Identifying technical and economic improvements to the MoneyMaker Hip Pump through multi-objective optimization. IEEE Global Humanitarian Technology Conference.