Senior Optimization Engineer (2D Glass Nesting & Inventory Logic)

@vishal1145

Your inventory logic is the bottleneck here. If the engine picks the wrong sheet from stock, you'll hit 85% yield instead of 98% - no matter how good the nesting algorithm is. I've seen this exact failure pattern in 3 glass fabrication projects where the optimizer worked perfectly in isolation but collapsed when connected to real-world inventory constraints. Before architecting the solution, I need clarity on two things: What's your current remnant tracking granularity - are you storing exact XY dimensions of every offcut, or just "small/medium/large" buckets? And what's the decision hierarchy when multiple sheets could theoretically hit 98% yield - do you prioritize oldest stock first, or purely by minimizing waste regardless of FIFO? Here's the architectural approach: - GENETIC ALGORITHMS + GUILLOTINE CUTS: Implement a two-phase optimizer where Phase 1 uses GA to test 500+ sheet combinations from inventory, then Phase 2 applies recursive guillotine partitioning with kerf compensation to validate each candidate hits 98%+ before committing. - POSTGRESQL INVENTORY INTELLIGENCE: Build a scoring function that queries available sheets, calculates theoretical yield for each using bounding box pre-checks, then runs full nesting only on the top 5 candidates to avoid computational waste. - FASTAPI + CELERY: Deploy the engine as an async microservice where long-running optimizations (30+ parts) run in background workers while returning real-time progress updates via WebSocket to prevent ERP timeouts. - JAVASCRIPT CANVAS RENDERER: Generate SVG cutting maps with color-coded kerf zones and part IDs that overlay directly onto your Bootstrap dashboard - I've built this exact visualization for a CNC router company processing 200 sheets daily. - IP TRANSFER PROTOCOL: Deliver fully documented Python codebase with unit tests covering edge cases like "what happens when no single sheet fits all parts" and "remnant smaller than minimum usable size" - plus Docker Compose setup for private server deployment. I've built 2 similar nesting engines for metal fabrication and leather cutting that achieved 97.8% and 98.4% yield respectively. The difference between 95% and 99% isn't just algorithm choice - it's handling the 47 edge cases where inventory constraints conflict with geometric optimization. Let's schedule a 20-minute technical call to walk through your current remnant data structure before I finalize the implementation plan.

@shadabkhan92

With years of experience in software development, particularly in optimizing and nesting algorithms, my team and I are well-equipped to tackle the intricacies of your project. We specialize in Python and C++, which align perfectly with your API and core engine requirements. Our command over Django, Flask, and MySQL would ensure seamless integration into your ERP system. In terms of algorithmic approach, our team intends to employ meta-heuristic strategies such as Genetic Algorithms or Simulated Annealing to achieve the desired 99% accuracy. We understand the importance of yield-based decision making and have extensive knowledge of computational geometry along with deep understanding of the "Cutting Stock Problem". Lastly, let me assure you that we take full responsibility for delivering clean, well-documented code and recognize that upon final payment, all rights will be transferred solely to you. We are excited about this project and believe our skill set combined with our experience in optimisation can bring immense value to your business. Looking forward to discussing further how we can contribute to this crucial undertaking!

@kaustubhbawa123

Hi, I am an IIT Grad, PMP Certified Professional, ex-BFSI and worked at fortune 500 companies. I will make it a reality for you. As a Senior Optimization Engineer Glass, I will develop a custom 2D glass cutting optimizer using mathematical engines like linear programming, quadratic programming, or convex optimization to achieve 98–99% material yield, utilizing industry-standard software tools and algorithms. Kindly click on the chat button so we can discuss and get started. Will share you my prior projects done and my resume too. I have been doing freelancing since 2019 worked at top MNCs in both USA and India. Lets connect

@MQamar123

My team and I, as highly skilled computational engineers, have all it takes to build a custom 2D Glass Cutting Optimizer that will significantly drive up your material yield. Our deep knowledge of Algorithms will be beneficial in building an efficient mathematical engine around your specific needs. We are experienced in implementing Big-Size-First and Best-Fit strategies for high-precision nesting and understand the significance of attaining accuracy levels of often-mentioned 98–99% through a recursive optimization approach. Lastly, our hands-on experience with Docker for local/private server hosting and DevOps knows no bounds. This will ease the transition process significantly when you need to host this cutting-edge engine on your private servers. Let's join hands in achieving notable results for your project through our unique blend of algorithmic sophistication and pragmatic engineering skills – together we’ll make each sheet count!

@letswork92

As a seasoned Algorithm Engineer with over 12 years of experience, I understand your need for a sophisticated 2D Glass Cutting Optimizer that achieves a remarkable material yield of 98-99%. Your project requires an intricate balance between inventory management and high-precision nesting—something that traditional web development cannot address. To tackle the "Cutting Stock Problem," I propose using a combination of Genetic Algorithms and Simulated Annealing to ensure optimal yield. My approach will involve scanning your PostgreSQL/MySQL database to intelligently select the best sheet size based on current inventory, prioritizing remnants while ensuring compliance with kerf and trim constraints. I can deliver the optimization engine as a FastAPI microservice in Python, complemented by a JavaScript component for real-time visualization within your Bootstrap interface. I fully agree to the transfer of all intellectual property and source code upon project completion. Could you elaborate on any specific performance metrics you'd like me to focus on during the development?

@UzeeTech

Having worked on numerous projects in the field of optimization and computation, I am confident in my ability to tackle your challenge head-on. My deep understanding of Computational Geometry and the "Cutting Stock Problem" will be the cornerstone of developing a custom 2D Glass Cutting Optimizer for your business that can achieve an impressive material yield of 98-99%. Throughout my career, I have showcased exceptional problem-solving abilities by implementing various algorithmic strategies. I also bring expertise in recursive optimization and meta-heuristics like Genetic Algorithms/Simulated Annealing that will be instrumental in achieving the high precision you require. Additionally, I have hands-on experience integrating complex backends (Python/Node.js) with frontends (Javascript/React), which will enable me to produce not just an efficient engine but also a user-friendly interface. What sets me apart from others is my commitment to open communication, clean documented code construction, and timely deliverables. Rest assured that as a serious bidder, wholeheartedly agreeing to the full transfer of Intellectual Property/Source Code unlike any general full-stack developer would do, I truly aim to provide an optimal solution tailored exclusively for you. By choosing me, you are making a decision towards maximum value and successful project completion. Let's make this project achieve its fullest potential!

@azwa04

Hi, I'M TOP RATED ON UPWORK I can easily DO your work IN 24 HOURS, DM me now to get started, PRICE NEGOTIABLE 100% Work satisfaction is provided

@jagratip3

Hi, This is not a typical dev task—it’s a Cutting Stock Optimization problem, and I’ve worked on algorithm-heavy systems involving bin packing, nesting, and meta-heuristic optimization. I can build a high-performance engine aligned with your 98–99% yield target. Algorithm Strategy (Core “Brain”): • Hybrid approach: Guillotine + Best-Fit + Meta-heuristics • Initial layout via Best Short Side Fit (BSSF) / Skyline heuristic • Refinement using Simulated Annealing + Genetic Algorithm for near-optimal packing • Strict handling of constraints: kerf, trim, rotation rules, multi-level guillotine cuts Inventory Intelligence (Key Differentiator): • Pre-process all sheets (jumbo, standard, remnants) • Score each sheet using: Yield % = (used area / sheet area) – penalty (waste, unusable fragments) • Prioritize remnants first with constraint-based filtering • Run parallel simulations per sheet type → select highest-yield candidate dynamically Architecture: • Core Engine: Python (FastAPI) or C++ (for performance-critical module) • Service Layer: REST API returning optimized layouts + metrics • Visualization: HTML5 Canvas (JS) for ERP embedding • Output: JSON (cuts, sheet usage, remnants, inventory updates) • Deployment: Docker-ready for private hosting Timeline: 4–6 weeks Budget: $2,000 – $3,000 I fully agree to Work-for-Hire + complete IP transfer. Best Regards, JP

@spodstechno

Dear [Client], I am excited to propose my expertise as a high-level Algorithm Engineer for the development of your custom 2D Glass Cutting Optimizer project. With a focus on achieving a material yield of 98–99% and a strong emphasis on ownership and IP rights, I am committed to delivering a robust mathematical engine that meets your requirements. The core functionality and logic, including Multi-Sheet Inventory Intelligence, will be meticulously implemented to ensure optimal results for your operations. Regards, Rahul Paspola

@indreshpnk

Hello, I understand you need a custom 2D Glass Cutting Optimizer with high-precision nesting, inventory intelligence, and 98–99% yield. The goal is to deliver a robust, production-ready optimization engine comparable to industry standards. Here’s what I can provide: Meta-heuristic based nesting (Genetic Algorithm + Best-Fit + BSF) with guillotine constraints, kerf, trim, and rotation handling. Smart inventory selection logic that evaluates all sheet sizes (including remnants) and chooses the highest-yield option dynamically. FastAPI/C++ microservice with JSON output + JS Canvas visualization integrated into your ERP. I bring 4+ years of experience in Python, Algorithms, and backend systems, with a strong focus on scalable and performance-driven solutions. I’ve worked on data-intensive and optimization-based systems ensuring efficiency and clean architecture. Just to clarify a few things: Do you have historical cutting datasets to tune the optimization model? Should the engine support real-time optimization or batch processing? Please come to the chat box to discuss more about your project. Best regards Indresh Kushwaha

@Royalitservices

Hi there, You’re absolutely in the RIGHT PLACE. I’ve delivered SIMILAR PROJECTS multiple times and know EXACTLY how to execute this efficiently and correctly from day one. To lock down the SCOPE, TIMELINE, AND PRICING, I’ll need to ask you a few key questions. Unfortunately, Freelancer’s 1500 CHARACTER LIMIT doesn’t allow me to break everything down properly here. Let’s jump on CHAT so I can show you my PROVEN PAST WORK, walk you through the REAL RESULTS I’ve delivered, and outline a CLEAR ACTION PLAN for your project. You’ll immediately see why my approach is DIFFERENT and EFFECTIVE. If you’re serious about getting this done RIGHT, I’m ready to move forward. Looking forward to CONNECTING and WINNING TOGETHER. Cheers, Mayank Sahu

@rishus283

I will develop high-quality custom software, web apps, or APIs for your business Description: Are you looking for a reliable software developer to bring your ideas to life? You're in the right place! I specialize in building scalable, efficient, and secure software solutions tailored to your needs. Whether you're a startup, business owner, or individual, I can help turn your vision into reality. What I offer: Custom software development Web application development (frontend & backend) REST API development & integration Bug fixing & performance optimization Database design & management Automation scripts and tools Technologies I work with: Languages: JavaScript, Python, Java, C++ Frameworks: React, Node.js, Django, Spring Boot Databases: MySQL, PostgreSQL, MongoDB Tools: Git, Docker, AWS Why choose me? Clean, maintainable, and scalable code Timely delivery and clear communication 100% client satisfaction focus Ongoing support after delivery Packages: Basic: Small bug fixes or simple scripts Delivery: 2 days Standard: Medium-sized web app or API Delivery: 5–7 days Premium: Full-scale application with advanced features Delivery: 10–14 days Note: Please contact me before placing an order so we can discuss your requirements in detail. Let’s build something amazing together!

@moinuddinB9

Hi there, Having worked on optimization engines that nail precision and efficiency, I’m confident I can meet your 98–99% material yield target. Your need for a clean, professional, and user-friendly solution feels right up my alley. You mentioned wanting a seamless integration with inventory intelligence and a dashboard that updates ERP inventory automatically—automated remnant prioritization and Best-Fit strategy using Guillotine cuts will ensure an integrated, highly efficient system. I specialize in Python-based algorithm development and building sleek JavaScript visual components, with Docker experience for smooth private hosting. I’m the right person because I provide clean, maintainable code and pride myself on fast, clear communication and speedy turnaround. Let me know if you are available for a quick chat! Regards, Moinuddin

@ARAVIND046

Hello, This is a computational optimization problem, and I have experience building similar systems. I will develop a hybrid optimization engine combining guillotine-based cutting with best-fit decreasing and big-size-first strategies, enhanced by genetic algorithms and simulated annealing to achieve near 99% utilization. A skyline-guillotine hybrid placement will ensure constraint compliance while maximizing yield. The system will include a yield-driven inventory engine that evaluates all available sheets, including remnants, through pre-simulation. It will prioritize off-cuts when efficient and select the sheet with the highest effective yield, minimizing waste and unnecessary jumbo usage. All constraints such as multi-level guillotine cuts, kerf, trim, and orientation rules will be handled accurately. The solution will be delivered as a FastAPI or C++ microservice with JSON output for layouts, utilization, and inventory updates. A JavaScript Canvas component will render cutting maps inside your ERP. The code will be clean, modular, Dockerized, and production-ready. I fully agree to the work-for-hire terms, with complete IP transfer upon final payment. Ready to proceed.

@NourhanSaleh1

I am an experienced Algorithm Engineer with expertise in Computational Geometry and the Cutting Stock Problem. For your 2D Glass Cutting Optimizer, I propose using a hybrid Guillotine + Meta-heuristic approach (Genetic Algorithm) to achieve 98–99% yield. The engine will intelligently scan your PostgreSQL/MySQL inventory, prioritize remnants, and select the optimal sheet per batch using yield-based decision logic. It will fully account for kerf, trim, and glass orientation. The solution will be delivered as a FastAPI (Python) microservice, with a JavaScript/HTML5 Canvas dashboard integrated into your Bootstrap 5 ERP. Docker deployment will ensure secure private hosting. I confirm full transfer of IP and source code upon final payment, with clean, documented, and maintainable code. This engine will be robust, scalable, and ready for real-world industrial usage.

@archanasoni1923

Hi I build optimization engines — this is exactly the kind of problem I work on. For the nesting core, I'll combine a Guillotine-cut tree with Simulated Annealing to consistently hit 98–99% yield. Big-Size-First handles initial placement; the meta-heuristic rearranges to close the gap. Kerf, trim, and orientation constraints are baked in from day one. For inventory selection, the engine queries your PostgreSQL stock, scores each available sheet by projected yield for the current batch, prioritizes off-cuts before Jumbo sheets, and picks the optimal match — not just the first fit. Delivery: FastAPI microservice + HTML5 Canvas renderer for your Bootstrap 5 ERP + JSON payload that auto-updates inventory and logs new remnants. Full IP and source code transfer on final payment — no reservations. Timeline: 8–10 weeks. Happy to walk you through the algorithm approach in a call before you decide. Bid amount is a placeholder and can be discussed over chat. Regards, Archana Soni

@karthikresonite

Hello, We specialize in optimization engines and computational geometry, and your 2D glass cutting requirement aligns with our core expertise. Algorithm Approach: We will implement a Hybrid Guillotine + Meta-Heuristic model: Initial Layout: Big-Size-First (BSF) with Skyline/Guillotine heuristics Optimization: Genetic Algorithm + Simulated Annealing to iteratively improve layouts and target 98–99% yield Full handling of kerf, trim, orientation constraints, and multi-level cuts (X/Y/Z) Inventory Intelligence: Real-time scan from PostgreSQL/MySQL Yield-based scoring across jumbo, standard, and remnants Remnant prioritization logic when efficiency ≥ threshold Dynamic selection of the best sheet per batch Technical Delivery: Core Engine: Python (FastAPI) or C++ microservice ERP Integration: JSON API + HTML5 Canvas renderer (JS) Inventory loop: auto deduction + remnant creation Deployment: Docker-ready for private hosting IP Agreement: We fully agree to 100% source code and IP transfer with clean documentation. Timeline: 8–10 weeks Why Us: Proven experience in optimization systems, scalable architecture, and high-performance logic design. Ready to discuss datasets and constraints in detail. Best regards, Resonite Technologies Team

@victorc309

I am an experienced Algorithm Engineer with expertise in optimization engines and cutting stock problems. To achieve 98-99% yield, I propose using Genetic Algorithms and Simulated Annealing for high-precision nesting, along with Best-Fit and Big-Size-First (BSF) strategies. Plan: - Inventory Lookup: The engine will scan PostgreSQL/MySQL databases, prioritize remnants, and select the best sheet for maximum yield. - API & ERP Integration: I’ll deliver the engine as a FastAPI microservice and provide a JavaScript canvas component for your ERP interface, ensuring smooth data flow via JSON. - IP Transfer: I agree to a full IP and Source Code transfer upon completion. I have the expertise to develop this solution with a focus on maintainability and efficiency. Best regards,