Smarter Scheduling with AI

nMetric has solved the age-old problem of complex scheduling.

Using an AI and Genetic Algorithm approach,
mediocre and needlessly constrained schedules are history.

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Meet our patented AI schedule engine.

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Genetic Algorithm Technology

nMetric spent several years developing a cutting edge, feature rich, and customizable scheduling engine based on the proven evolutionary algorithm technique known as a Genetic Algorithm.

Using all their experience from decades in the scheduling software market, the new GA Scheduling Engine is better than every other scheduling software on the market - by far. 

nMetric's engine uses the dynamic and learning GA to find optimal schedules no matter the complexity. Traditional engines depend on static and deterministic algorithmic logic that can't handle complexity or complicated requirements.

Our patented genome representations allow for fast and efficient handling of complex environments and constraints. Multi-level and multi-resource requirements are handled effortlessly by the scheduling engine.

Designed from the ground up, based on decades of scheduling software development and manufacturing experience. 

nMetric's GA allows for multiple objective scheduling - users can balance their priorities instead of focusing on just lateness or just lag-time.

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Schedule Generation with the Genetic Algorithm

The nMetric GA Scheduling engine generates thousands of virtual schedules based on survival-of-the-fittest philosophy. It generates the best schedules because it adapts to every requirement to get things done on time. 

Flexible scheduling with real-world constraints like dispatch zones, term fences, and locked sequences are easily defined and represented. 

Designed from the ground up to be a plug-in solution with MES/ERP/MRP systems, the engine is stand alone and can run with even a minimal amount of data.

The engine is multi-threaded and cloud based, allowing for efficient and near real-time scheduling to even the largest schedules.

Schedules are updated with each translation, so all users and stakeholders are informed and up-to-date.

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Making the "BEST" Schedule

The problem with traditional scheduling engines is that they're very limited in their definition of a "best" schedule - they can't adapt to every company's individual, and very important, preferences.

Every company has a different definition of "best" - nMetric's GA allows users to configure their constraint preferences and the engine creates schedules that balance their priorities to produce shockingly good schedules. 

The technical term is "Multi-Objective Optimization" but what it means is that the engine can balance lateness, earliness, lag-time, max-early, and many other preferences to get a schedule that meets their requirements to get the optimal schedule.

These preferences can be set up once (set it and forget it) and run for years, or updated whenever the situation demands. 

Individual priorities can be adjusted for orders, customers, and resources, letting the engine find the best combination.

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The GA is fast and efficient


Under the hood, the nMetric GA Scheduling Engine generates and compares hundreds to thousands of virtual schedules in its search to find the most optimal schedule. 

The GA, by its very nature, is scalable and allows for efficient parallel processing to generate schedules.

At its core, the engine is a cloud software application, but it can be deployed to secure or private environments without an issue. 

Initial genomes are created using simple and direct techniques to make even the first generations of virtual schedules produce very good schedules, so as the engine learns, they get even better.

The engine also uses the best schedules from previous runs, so it doesn't start from scratch each time.

Adding, removing, completing, and canceling jobs happens continuously in scheduling, and the GA seamlessly integrates these changes into the schedule.

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Moving AI from Theory to Production

Using Genetic Algorithms to Revolutionize Manufacturing Scheduling

Advances in artificial intelligence (AI) are driving groundbreaking innovations across industries, yet manufacturing has been slow to embrace AI due to the challenges of adapting conceptual models to real-world constraints. This paper examines how nMetric’s genetic algorithms (GAs) and SmartJob technology are transforming manufacturing scheduling by addressing the complexities of dynamic, large-scale industrial environments.

Challenges in Traditional Scheduling: Manufacturing scheduling faces resource allocation issues, conflicting goals, and rapidly changing conditions. Traditional methods struggle with the high-dimensional, nonlinear, and multi-objective nature of these problems. GAs excel by using natural selection principles to improve solutions iteratively.

nMetric’s GA Framework: nMetric’s framework integrates GAs with innovations like tailored chromosome representations, fitness functions, and patented genetic operators. Case studies show improved throughput, flexibility, and resilience over traditional methods.

From Theory to Practice: nMetric bridges the gap between AI theory and real-world applications, demonstrating how GAs can revolutionize smart manufacturing with production-ready systems.

Scalability and Real-Time Integration: nMetric’s GA Scheduling Engine combines scalability, adaptability, and cost-efficiency with real-time data and hybrid AI for enhanced decision-making and AI adoption.

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Additional features of our
AI / Genetic Algorithm Engine

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Multi-Objective Flexibility

Customizable fitness factors generate truly optimized schedules.

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Complete Optimization

Explores the entire solution space to find schedules traditional methods miss.

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Expert Knowledge

Built on decades of real-world scheduling expertise for reliable performance.

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Non-Deterministic Optimization

Delivers faster, nonlinear scheduling compared to traditional algorithms.

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Scalable & Parallel Processing

Supports multi-threaded and cloud-based implementations for unmatched scalability.

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Evolutionary AI

Mimics natural selection, using "survival-of-the-fittest" to refine schedules continuously.

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Dynamic & Responsive

Adapts quickly to changes in orders, resources, and priorities by leveraging past schedules.

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Patented Innovation

Employs multiple GA scheduling patents to bridge the gap between theory and practice.

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Smart Scheduling Methods

Beyond industry-standard approaches, nMetric incorporates innovative methods to address complex scheduling challenges effectively.

Schedule a demo to see how our engine can create your best schedule

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