Python Optimization Engine Developer

@MashoodurRehman1

I am a seasoned Python developer with extensive experience in optimization algorithms and linear programming, making me well-suited for developing your Cutting Stock optimization engine. My proficiency with Google OR-Tools and PuLP enables me to efficiently tackle the linear programming requirements specified in your project. My background includes designing and implementing REST APIs, which aligns with your need for integration using APIs/webhooks. Furthermore, I have a deep understanding of bin-packing algorithms and their applications, which will be crucial for automating roll-stock two-knife order pairing. My experience in supply chain optimization, particularly within manufacturing environments, enhances my ability to deliver a robust solution tailored to your business needs. I am keen to discuss how my skills can contribute to the success of your project. Could you share more about any additional features or constraints you envision for the optimization engine?

@opencollar

Hi, I notice your project needs to cut waste and make the best use of stock, which is like fitting puzzle pieces together. I can handle the optimization logic with Python using OR-Tools or PuLP, and I’ll also set up easy APIs for smooth data exchange. Do you want the system to also suggest alternative packings if the first plan isn’t perfect? Let’s chat about a plan and build something great together. Regards, Nick. I’ve worked on projects like the multivendor marketplace, a fleet management system, and a ticketing app that all required tight API integration and smart algorithms.

@extreamcode

Hello, I can see the core challenge here isn’t just writing Python , it’s turning messy production constraints into reliable cutting decisions your team can trust. I’ve built Python-based API workflows and optimization logic with OR-Tools/PuLP-style approaches, and I can structure this engine to handle linear programming, roll-stock pairing, and webhook/REST integration cleanly. I’ll focus on accuracy first, then make sure the output is practical for corrugated manufacturing operations. I’ve shared an initial estimate based on your description, and once we go over a few technical or functional details, I’ll confirm the exact cost and delivery schedule. If you already have sample orders, stock dimensions, and pairing rules, I can map the model quickly and propose the best formulation. Looking forward to your reply so we can finalize the exact plan. What inputs and constraints should the optimization engine prioritize first: sheet width, knife limits, waste reduction, or order batching rules? Best regards, Asad

@shrec

Hi, I can help you with your project and deliver a high-quality result that meets your requirements. I have experience solving similar problems and focus on clean work, timely delivery, and clear communication. I will carefully review your needs, suggest the best approach, and keep you updated throughout the process. I am ready to start and would love to discuss more details about your project. Best regards

@kamran2012

Interesting project, I will build your Cutting Stock optimization engine using Google OR-Tools for the linear programming core, with bin-packing logic handling two-knife order pairing against your roll-stock widths. You will get a clean REST API layer ready for webhook integration with your existing corrugated manufacturing systems. On a similar optimization build for material yield, structuring the LP model to minimize trim loss across variable roll widths produced measurable waste reduction within the first production cycle. Questions: 1) How many standard roll widths does the engine need to optimize against, and do width combinations change frequently? 2) Will the API integrate with a specific ERP or MES system, or is this standalone for now? Looking forward to potentially working together. Thanks, Kamran

@InterconnectBPO

I can develop a robust Python-based Cutting Stock optimization engine tailored for your corrugated manufacturing needs. My approach will focus on ensuring optimization algorithm accuracy while integrating seamlessly with your existing systems. Your emphasis on Linear Programming using tools like Google OR-Tools or PuLP aligns perfectly with my skill set. I understand the importance of APIs and will implement RESTful services to facilitate smooth integration. My expertise in Python and extensive experience with API integrations make me a strong candidate. We have 20+ 5-star reviews on similar projects! I look forward to discussing how I can contribute to your project. Regards, InterconnectBPO

@corpmember29

Hello, I have carefully reviewed your requirements and understand that you need a high-accuracy Cutting Stock Optimization Engine for corrugated manufacturing using Linear Programming and efficient bin-packing algorithms with seamless REST API integration. I have 13+ years of experience in Python development, optimization algorithms, REST APIs, and industrial automation solutions. I can develop an optimization engine using Google OR-Tools (preferred) or PuLP to maximize material utilization, automate two-knife roll-stock pairing, minimize waste, and expose secure REST APIs/webhooks for easy integration with your existing systems. The solution will be modular, well-documented, and optimized for performance and scalability. I recommend Python with Google OR-Tools, FastAPI, and PostgreSQL to deliver a fast, maintainable, and production-ready optimization platform. I WILL PROVIDE 2 YEARS OF FREE ONGOING SUPPORT, COMPLETE SOURCE CODE, AND ASSIST YOU FROM DEVELOPMENT TO SUCCESSFUL DEPLOYMENT. I am available to start immediately and look forward to discussing your optimization requirements in detail. I eagerly await your positive response. Thanks, Christina

@Hubready

Hello!, I am a US-based senior software engineer(frontend, backend, ecommerce, etc) with 15+ years of experience in Python, software architecture, linear programming, operations research, and API development. I read your Cutting Stock optimization engine project carefully, and I understand the main goal is to build a practical engine for corrugated manufacturing that generates reliable, profitable cut plans. Could you please clarify the following questions to help me better understand the project? 1) What input data will the engine receive, sheet sizes, orders, flute specs, waste rules, and machine constraints? 2) Do you want a pure optimization engine first, or a full REST API with validation and reporting from day one? 3) Should the solution optimize for maximum yield, minimum waste, production speed, or a weighted mix? My approach would be: first map your business rules and constraints, then design the optimization model, then build the Python engine, and finally expose it through a clean REST API with tests and edge cases covered. I’ve built similar production systems where accuracy and performance mattered, so I know how important it is to get the logic right the first time. Relevant examples of work: - Production planning optimizer for a packaging workflow - Inventory allocation engine for a manufacturing system - Python REST service for order routing and constraints - Scheduling tool for logistics operations If you want, I can help turn this into something clean,

@kabirchy

Hi there, I’ll build a robust Cutting Stock optimization engine tailored for corrugated manufacturing using Google OR-Tools — chosen for its speed, scalability, and native support for integer programming (critical for trim-loss minimization). The engine will model 1D/2D cutting patterns with constraints like raw material widths, order priorities, and machine-specific limits. I’ll expose it via clean REST APIs (Flask/FastAPI) supporting JSON-based job submission, status polling, and webhook callbacks for async result delivery. All endpoints will include input validation, error handling, and logging. The architecture separates optimization logic from API layer for maintainability and future scaling — e.g., adding batch processing or cloud deployment later. I’ve delivered similar OR solutions for packaging and sheet metal industries, where real-world constraints like skids, pallet limits, and setup time were embedded directly into the LP models. I’ll also provide clear documentation and a lightweight CLI for local testing. Best Regards, Khorshed Alam, RS Software

@koolvishruth

Hi Sir, I have 7 years of experience in Python and API development.I can work on optimising your algorithm as mentioned and also can implement webhook . Let’s connect

@devendrathakur12

Hello I have gone through your specific requirement for Cutting Stock engine. I would use column generation instead of a plain LP because it keeps solving larger cutting patterns without slowing down as orders grow. I will build a Python service with REST APIs that finds better roll pairing while keeping waste low. But first I want the rules matching your factory flow. I built optimisation tools for logistics clients and improved planning across 10000 plus records. Private work, screenshots and code walkthrough I can share. How are cutting rules decided today? I want to understand machine limits and order priority. Free for a quick chat this week? Dev Singh

@sufyanasmat38

With over a decade of experience in software engineering, AI and machine learning, Fourge is well-positioned to tackle your project. We have extensive expertise in Python and optimizing software for a variety of business purposes. Our familiarity with Linear Programming, Google OR-Tools, PuLP and bin-packing algorithms aligns perfectly with your requirements, giving you the confidence that we can execute an accurate and efficient cutting stock optimization engine. Moreover, our proficiency in API integrations including REST API will allow us to seamlessly integrate your optimization engine with other systems in your manufacturing setup, enabling smooth data transfer and enhanced operational efficiency. Our ability to employ different techniques like we did previously (for clients with various needs) proves that we can adapt and find the best solution for any scenario. Our multidimensional approach sets us apart. In addition to technical prowess, we come bearing experience - we understand complex optimizations in manufacturing and supply chains. These hands-on insights enable us to map our technology to your unique business needs from concept to deployment. Once we understand your specific challenges and goals, we'll develop a solution tailored to improve your efficiency while reducing costs. Let's join forces on this endeavor for optimal results!

@C0RETECHIES

Hi there, You need a cutting stock optimization engine for corrugated manufacturing. Operationally, it will take a list of orders (dimensions, quantities) and available master roll inventory, then apply a linear programming model to generate an optimal cutting plan. This plan, designed for a two-knife process, aims to minimize material waste by intelligently pairing orders onto rolls and will be accessible via a REST API for workflow integration. Technical approach: The core will be a Python service using Google OR-Tools for its linear programming solver. We'll wrap this logic in a lightweight FastAPI application to serve a clean REST API. The mathematical model will be a variation of the classic bin-packing/cutting stock problem, focused on minimizing trim loss. Core modules: The engine will consist of an API endpoint for job submission, a data validation layer for orders/stock, a dynamic model generator that builds the LP problem in OR-Tools, the core solver execution, and a results formatter that returns the final cutting plan as structured JSON. Implementation strategy: We'll start by developing and validating the core optimization algorithm on a defined test case. Following that, we will build the API wrapper. We'll then iteratively introduce more complex constraints (e.g., multiple stock widths) and ensure performance before deploying the engine as a containerized service for easy integration. 1. What is the typical number of unique order sizes and master roll widths in a single optimization run? 2. Are there secondary objectives besides minimizing waste, like reducing the number of cutting pattern changes? 3. How should overproduction be handled? Is it permissible to exceed order quantities if it leads to more efficient roll usage? Regards, Rohit

@denisSolution

Hi, The project needs a Python-based optimization engine that accurately solves a Cutting Stock problem for corrugated manufacturing, where raw roll-stock is cut into smaller pieces while minimizing waste. I’ve built similar LP-based optimization systems before, like a nesting engine for sheet metal cutting that reduced material waste by 15%—though it required fine-tuning the solver parameters to balance speed and precision. I’d approach this using OR-Tools’ LP solver paired with a bin-packing layer for order pairing, since it keeps the solution deterministic while avoiding brute-force combinatorics. The biggest improvement will come from validating the algorithm against real production constraints, like knife limits and roll widths. I’ll keep the API layer clean and versioned, so integrations stay stable even if the optimization logic updates. Testing against historical orders will ensure the engine meets the accuracy priority before anything ships. The goal is a reliable system that reduces material waste and speeds up production planning without constant manual tweaks. If this fits, I can start right now. Thanks, Denis.

@ShaikhAneesa

Hi there, I understand you're looking for a Python-based Cutting Stock optimization engine for corrugated manufacturing that accurately minimizes material waste while automating two-knife roll-stock order pairing and integrating seamlessly with your existing systems. I'm confident I can build a scalable, production-ready solution focused on optimization accuracy and performance. My approach is to develop the optimization engine using Google OR-Tools (or PuLP if preferred), combining Linear Programming with efficient bin-packing algorithms to generate optimal cutting patterns and automate roll-stock pairing. I'll expose the engine through secure REST APIs/webhooks for easy integration with your ERP or production systems, ensuring fast processing, configurable constraints, and maintainable code. The solution will include validation, detailed optimization outputs, comprehensive documentation, and be designed to accommodate future production rules or machine constraints. Deliverables include the optimization engine, REST API integration, automated pairing logic, source code, testing, deployment guidance, and complete technical documentation. Could you clarify whether the optimization should support multiple stock widths and machine-specific cutting constraints (minimum trim, knife limits, etc.), or will all orders follow a single production configuration? I'm ready to start immediately. Warm Regards, Aneesa.

@mayankinnovative

Having read and understood the intricacies of your project, I bring to the table not only my expertise in Python programming, but also a deep understanding of optimizing complex processes. Whether it is employing Google OR-Tools or PuLP for Linear Programming, implementing REST API for webhooks and integration, or utilizing bin-packing algorithms for roll-stock two-knife order pairing automation, my skills align perfectly with your project requirements. With a 20+ year experience in PHP-based development, I have a proven record of delivering robust and highly functioning systems across various industries. My background in supply chain optimization means that I resonate deeply with the manufacturing process you are describing and ensures that I'm able to apply your specific needs most effectively. I believe in solutions that are not just functional, but also maintainable and scalable, which can be evidenced by the long-term relationships my clients build with me. I'm driven by the goal of providing results that don't just meet expectations but constantly exceed them. Hiring me would ensure a smooth development process where your project remains stable and increasingly optimized over time.

@gowthamsarathy

Hello, My approach is to model the cutting stock problem as a Linear Programming optimization engine using Google OR-Tools (or PuLP where appropriate), combining column generation and bin-packing heuristics to minimize trim waste while maximizing material utilization. I'll design the solver as a modular Python service with separate optimization, validation, and API layers, exposing REST endpoints/webhooks for seamless ERP/MES integration. The engine will support configurable constraints (roll widths, knife limits, order priorities, and production rules), generate optimized cutting patterns, and return detailed optimization metrics with comprehensive logging for traceability and future tuning. One technical question: Could you share the operational constraints for your two-knife pairing process (maximum roll width, knife limitations, and any order priority/business rules) so the optimization model can accurately reflect your production environment? I have strong experience building Python-based optimization, automation, and API-driven systems with a focus on performance, maintainability, and clean architecture. I can deliver the optimization engine, REST API, documentation, and integration support. The quoted price is an initial estimate and can be adjusted after reviewing the complete requirements and production constraints. Best Regards

@TeraByte26

Hi, I will deliver a Cutting Stock optimization engine with Linear Programming and REST API integration, prioritizing optimization algorithm accuracy, and I will complete it within the 1500-3000 USD budget, can you confirm the deadline? Waiting for your response in chat! Best Regards.

@teodorgeorge

Hello, I work with Python optimization tools for planning problems where Linear Programming accuracy matters. Your Cutting Stock engine fits my experience with Operations Research, bin-packing logic, and API Integration for production workflows. I will model roll-stock two-knife order pairing, compare OR-Tools or PuLP, and validate results against corrugated Manufacturing constraints. Then I will expose the engine through a clean REST API and webhooks so your system can automate pairing decisions reliably. Best regards, Teo