Batch Mix Combination Optimizer
Budget: ₹37,500 – ₹75,000 INR
I want a web-based application that takes my existing product list and, much like a flight-search engine, explores every feasible permutation and combination to build the best possible batch mix. The engine must calculate against the key criteria of Quality, Cost and Quantity—with the flexibility to layer in additional factors such as ageing, size or any future attribute I might add.
How it should work
• I upload or paste a CSV / Excel list containing product codes, available stock, unit cost, quality grade and any other relevant fields.
• Through an on-screen dashboard I set or adjust the preference weights (e.g., “give quality twice the importance of cost” or “reject any mix below a minimum quantity”). No coding should be required on my side; sliders, dropdowns or similar UI controls are perfect.
• On submission the back-end (Python with itertools, OR-Tools, or another optimisation library you prefer) generates all viable mixes, ranks them by my current preferences and returns a clear, paginated results table. Each result should detail overall quality score, total cost, total quantity, and a breakdown of the chosen items.
• I can export the selected mix in CSV or Excel, or simply copy it to the clipboard.
Tech notes
– Python is preferred for its rich optimisation libraries, but I’m open to alternatives if they serve performance and maintainability.
– A lightweight web stack—FastAPI / Flask on the back-end and a simple React or plain-HTML/JS front-end—is ideal, but again I’m flexible.
– The code has to be clean, documented and handed over so my team can extend the criteria list later.
Acceptance criteria
1. Web interface loads locally or on a small cloud instance with no manual setup other than “pip install -r requirements.txt”.
2. Preference weights can be changed in real time and immediately re-rank results.
3. Engine consistently returns the mathematically optimal mix for the provided data set and constraints (I will supply a test sheet for validation).
4. Export of the chosen mix works flawlessly in CSV and XLSX.
If you have built scheduling, packing, or optimisation tools before and can demonstrate a quick proof of concept, let’s talk.
How it should work
• I upload or paste a CSV / Excel list containing product codes, available stock, unit cost, quality grade and any other relevant fields.
• Through an on-screen dashboard I set or adjust the preference weights (e.g., “give quality twice the importance of cost” or “reject any mix below a minimum quantity”). No coding should be required on my side; sliders, dropdowns or similar UI controls are perfect.
• On submission the back-end (Python with itertools, OR-Tools, or another optimisation library you prefer) generates all viable mixes, ranks them by my current preferences and returns a clear, paginated results table. Each result should detail overall quality score, total cost, total quantity, and a breakdown of the chosen items.
• I can export the selected mix in CSV or Excel, or simply copy it to the clipboard.
Tech notes
– Python is preferred for its rich optimisation libraries, but I’m open to alternatives if they serve performance and maintainability.
– A lightweight web stack—FastAPI / Flask on the back-end and a simple React or plain-HTML/JS front-end—is ideal, but again I’m flexible.
– The code has to be clean, documented and handed over so my team can extend the criteria list later.
Acceptance criteria
1. Web interface loads locally or on a small cloud instance with no manual setup other than “pip install -r requirements.txt”.
2. Preference weights can be changed in real time and immediately re-rank results.
3. Engine consistently returns the mathematically optimal mix for the provided data set and constraints (I will supply a test sheet for validation).
4. Export of the chosen mix works flawlessly in CSV and XLSX.
If you have built scheduling, packing, or optimisation tools before and can demonstrate a quick proof of concept, let’s talk.
Related categories:
PHP
JavaScript
Python
Algorithm
Excel Macros
Flask
Data Visualization
Data Analysis
Performance Tuning
FastAPI