Package neqsim.process.util.optimization
package neqsim.process.util.optimization
Optimization utilities for batch studies and parameter screening.
This package provides tools for systematic exploration of design spaces:
- BatchStudy: Parallel execution of parameter variations
- Multi-objective: Compare cases by CAPEX, OPEX, emissions, etc.
- Cloud-ready: Designed for horizontal scaling
- Result Export: CSV output for further analysis
Typical Use Cases:
- Field development concept screening
- Design optimization studies
- Sensitivity analysis
- Operating envelope mapping
Usage Example:
BatchStudy study = BatchStudy.builder(process).vary("compressor.pressure", 30.0, 80.0, 10)
.vary("cooler.temperature", 20.0, 40.0, 5).addObjective("power", Objective.MINIMIZE,
p -> ((Compressor) p.getUnit("compressor")).getPower("MW"))
.parallelism(16).build();
BatchStudyResult result = study.run();
result.exportToCSV("screening_results.csv");
- Version:
- 1.0
- Author:
- ESOL
- See Also:
-
ClassDescriptionParallel parameter study for rapid concept screening.Results of a batch study.Builder for BatchStudy.Result of a single case.Optimization direction.Definition of an objective.A set of parameter values for one case.Definition of a parameter variation.Loader for lightweight YAML/JSON optimization specs that map onto scenarios.Constraint representation inside the spec.Objective representation inside the spec.Scenario configuration from YAML.Spec root.Variable representation for manipulating streams.Utility class for production optimization based on capacity utilization and configurable constraints.Function to compute capacity duty/limit for a specific equipment.Range container to support percentile-based capacity evaluations.Pair of capacity duty/max providers.Direction of a constraint comparison.Severity classification for constraints.Outcome for a single constraint evaluation.Constraint template applied to each matching equipment.Metric to evaluate per-equipment constraints.Result of a single iteration.Snapshot of each iteration to support diagnostics and plotting.Definition of a manipulated decision variable.Objective optimization direction.Builder-style configuration for the optimizer.Simple container for constraint configuration.Simple container for objective configuration.Result container for a completed optimization attempt.Lightweight summary of an optimization run intended for quick-consumption APIs.Per-scenario KPI values and deltas versus the baseline scenario.Definition of a KPI to report alongside scenario comparisons.Scenario definition to enable side-by-side optimization comparisons.Optimization result paired with a scenario name to aid reporting/comparison.Supported search algorithms.Holds the utilization status for an equipment item.Series-friendly representation of utilization across iterations for plotting/reporting.