Quantum Modeler · Job Scheduling

Job Scheduling

Check whether fixed-machine operations can fit a discrete time horizon with job precedence and no machine overlap. This model checks feasibility; it does not minimize makespan.

Execute at most 8 total qubits using an ideal classical statevector simulator. Symbolic scaling does not execute or solve a larger instance.

Build your problem

Presets replace problem inputs. Your execution and projection settings stay as entered. Edit any input, then build to calculate new results.

Every possible operation start consumes one decision qubit. At most 8 total start variables are executable. Operations are nonpreemptive and follow their order within each job.

Problem inputsMachine countTime horizonOperations — job machine duration, one per lineJob and machine indices start at zero. Jobs have no gaps. Row order within each job defines precedence. Durations are integer time units from 1 through the horizon.

Large-target projection (optional)

Leave all target fields blank for this exact encoded input. Enter independent target statistics to estimate resources; only the small instance is executed.

Grey examples are suggestions; enter values for your own target.Target operations (across all jobs)Target time horizonOptional duration histogram — duration count, one bin per lineSupply both target size fields. Histogram counts must sum to the target operation count; durations must fit the target horizon. Without a histogram, variable counts are upper bounds. No machine assignments or job precedence are inferred.

Use the Quantum Compiler for native compile-only inputs within its resource limits. A projection does not construct or compile the target.

Execution settingsMeasurement shotsSampling seed

Depth 1 QAOA, at most 64 parameter evaluations. One completed build uses one run when usage limits are enabled.

Qubit budget

All decision and auxiliary variables count toward the limit. The API validates all constraints before reserving a run.

Read the mathematical methodology

Ready to validate a small instance.

Results describe the last completed build.

Explain this model

EXECUTED

Small-instance simulation

VERIFIED

Independent classical reference

ENCODING RESOURCES

Encoded input resources

Sampled states

Bits	Count	Probability	Penalized energy	Feasible objective	Penalty constraints	Assignment

Full probability distribution

Bits	Count	Probability	Penalized energy	Feasible objective	Penalty constraints	Assignment

Circuit artifacts

x0 is the leftmost assignment bit. Measurements map xi → q[i] → c[i]; tools displaying c[N−1]…c[0] require register-order conversion.

Open in Simulator

Variable mapping

QUBO and Ising coefficients

Generated DSL

OpenQASM 2.0

Routing and scheduling models

TSP · Job Scheduling · Vehicle Routing. Tiny validated examples execute within eight total qubits; larger inputs use the Problem Compiler.

No quantum advantage, real-QPU performance, physical-qubit requirement, or production-scale solution quality is claimed.