WiraSolver — Advanced Scheduling & Optimization Engine
WiraSolver is Wirabumi’s vision for an advanced production scheduling and optimization engine built for complex manufacturing environments. It is designed to solve multi-constraint planning problems such as capacity balancing, sequencing, material availability, and delivery commitment.
Unlike traditional ERP scheduling modules that rely on static priority rules or manual sequencing, WiraSolver is built on formal optimization techniques from operations research and computer science.
The engine models production planning as a constrained optimization problem — incorporating finite capacity scheduling, precedence constraints, setup time dependencies, and material availability rules.
Depending on problem scale and complexity, WiraSolver applies a combination of:
- Constraint-based modeling
- Heuristic and metaheuristic search strategies
- Iterative improvement algorithms
- Simulation-driven validation
The objective is not just to generate a schedule, but to compute a feasible and optimized production plan under real-world manufacturing constraints — balancing throughput, lead time, and resource utilization.
A Simple Example of the Problem We Solve
Consider a simplified production scenario:
You have:
- 2 machines (M1, M2)
- 3 jobs (J1, J2, J3)
- Each job must pass through both machines
- Each machine can process only one job at a time
- Each job has a due date
Processing time (in hours):
| Job | M1 | M2 | Due Date |
|---|---|---|---|
| J1 | 2 | 3 | 8 |
| J2 | 4 | 2 | 7 |
| J3 | 3 | 1 | 6 |
The goal is not just to “schedule everything.”
The solver must:
- Decide job sequence on M1
- Decide job sequence on M2
- Respect machine capacity constraints
- Ensure job order consistency
- Minimize total lateness or makespan
Mathematically, this can be represented as:
Minimize:
Total Lateness = Σ max(0, Completion Timeᵢ − Due Dateᵢ)
Subject to:
- Each machine processes only one job at a time
- A job cannot start on M2 before it finishes on M1
- No job overlaps on the same machine
Even in this small example, the number of possible sequences grows factorially.
With 3 jobs → 6 possible sequences.
With 10 jobs → 3,628,800 possibilities.
With 20 jobs → astronomically large search space.
This is why production scheduling is not a spreadsheet problem.
It is a combinatorial optimization problem.
What WiraSolver Does
WiraSolver evaluates feasible sequences using constraint modeling and guided search techniques. Instead of testing all possibilities exhaustively, it:
- Prunes infeasible schedules early
- Uses heuristic scoring to guide exploration
- Iteratively improves candidate solutions
- Validates feasibility against material and capacity constraints
The result is a production schedule that is:
- Feasible
- Computed under real constraints
- Optimized for defined business objectives
Engineering Production Intelligence
Manufacturing complexity does not disappear as a company grows — it multiplies. More machines, more product variants, tighter delivery windows, and higher cost pressure turn scheduling into a strategic decision, not an operational afterthought.
WiraSolver represents our commitment to engineering-grade production optimization — grounded in formal modeling, constrained computation, and algorithmic rigor. It is not a rule-based scheduler. It is a structured solver designed to operate within real-world manufacturing limits.
This is our long-term direction: intelligent manufacturing systems where planning decisions are computed, validated, and continuously improved — not guessed.