Bin Packing & Cutting Stock Optimization Expert

Project Overview We are seeking one or two highly specialized experts in combinatorial optimization to design, implement, and validate production-grade cutting stock and bin packing algorithms for integration into our supply chain and logistics platform. This is a technical engagement requiring deep applied mathematics expertise alongside strong C++/C# engineering skills. Rather than committing to a full-scope engagement up front, we have structured this work into four discrete, gated stages. Each stage produces a defined deliverable and a clear go/no-go decision point, allowing both parties to assess fit and progress before proceeding further. This structure protects our investment and gives you a clear runway to demonstrate value. What We Are Building Our platform handles real-world supply chain and logistics operations, including material planning, shipment consolidation, load optimization, and production scheduling. We have identified a critical gap: our current approach to cutting stock and bin packing is suboptimal, resulting in material waste, excess shipping cost, and missed consolidation opportunities. We need algorithms that: ● Handle 1D, 2D, and/or 3D variants of the cutting stock and bin packing problem (scope to be confirmed in Stage 1) ● Perform at production scale — real-time or near-real-time response for typical problem sizes encountered in our environment ● Integrate cleanly into our existing C++ codebase and data models ● Are configurable to our specific constraint sets (item dimensions, stock types, grouping etc.) ● Produce solutions that can be explained and validated by domain stakeholders, not just a black box score Who We Are Looking For We are open to a single expert or a complementary two-person team. The ideal profile combines rigorous OR/algorithm depth with hands-on C++ engineering experience in an industry context. Specifically, we need: Must-Have ● Degree in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or a closely related field ● Demonstrated expertise in solving related problems ● Strong C++ proficiency: production-quality, well-structured code, not prototype scripts ● Experience delivering optimization solutions in an industry setting (not purely academic) — supply chain, logistics, manufacturing, or distribution preferred ● Ability to work from specifications, ask sharp clarifying questions, and produce written documentation of design decisions Strongly Preferred ● Familiarity with the literature on exact methods as well as heuristic and metaheuristic approaches ● Prior work integrating OR algorithms into production software stacks ● Understanding of supply chain and logistics domain constraints — demand variability, stock availability, order sequencing, and cost trade-offs ● Supply-chain knowledge Team Structure We are open to: (a) a single senior expert who covers both algorithm design and C++ implementation; or (b) a two-person team pairing an OR specialist with a C++/C# engineer. If proposing a team, please describe how responsibilities will be divided and how the collaboration will be managed. Staged Engagement Approach The engagement is structured in four stages. We will evaluate deliverables and issue a decision before proceeding to the next stage. This structure reduces our risk and yours — we are not asking for a fixed-price bid on a scope neither party fully understands yet. Stage 1: Specification Review & Effort Estimation You will receive our current technical specifications, data samples, constraint documentation, but you will have no access to our existing algorithms or documentation. Your task is to evaluate what we have, clarify what is ambiguous, and produce a written assessment of scope, approach, and effort. Key Deliverables: ● Written review of our specifications, data models, and constraints ● Recommended algorithmic approach(es) with rationale (e.g., exact vs. heuristic, 1D vs. 2D scope) ● Effort estimate broken down by stage, including assumptions and key risks ● Identification of any gaps in our current specifications that must be resolved before development begins ● Questions and clarifications log ⛳ Go/No-Go Gate: We review the Stage 1 deliverables together. If the approach and estimate are aligned, we proceed to Stage 2. Stage 1 is compensated regardless of outcome. Stage 2: Algorithm Design & Development Using the agreed approach from Stage 1, you will gather existing open source models, redesign them (Or start from scratch) and implement the core optimization algorithms. This stage is contained to algorithm logic — standalone, testable, and benchmarked against defined performance targets — before any integration into our stack. Key Deliverables: ● Fully implemented C++ algorithm(s) for the agreed problem variant(s) ● Benchmark results against defined test cases and problem sizes, including solution quality and runtime metrics ● Documentation of algorithm design, key parameters, and tuning guidance ● Unit test suite covering correctness and edge cases ● Comparison against our current baseline (if applicable) ⛳ Go/No-Go Gate: We validate algorithm performance against agreed benchmarks and acceptance criteria. If targets are met, we proceed to Stage 3. Partial progress that falls short of targets is evaluated on a case-by-case basis. Stage 3: Integration into Production Stack The validated algorithms are integrated into our existing C++ codebase, connected to our data models and APIs, and made configurable to our operational parameters. This stage assumes close collaboration with our internal engineering team. Key Deliverables: ● Integrated algorithm module within our codebase, following our code standards and architecture ● API or interface layer connecting the optimizer to our data inputs and outputs ● Configuration layer exposing tunable parameters to operations users ● Integration test suite verifying end-to-end behavior with live or representative data ● Updated documentation reflecting integration design ⛳ Go/No-Go Gate: We run internal QA and integration testing. If the integration meets functional requirements, we proceed to Stage 4. Stage 4: Testing, Validation & Efficiency Proof The integrated solution is validated against real operational data and business metrics. This stage produces the evidence needed to confirm the investment delivered measurable value and to identify any final tuning required before full production rollout. Key Deliverables: ● Validation report comparing optimization outcomes against our current baseline across representative operational scenarios ● Quantified efficiency improvements: waste reduction, cost savings, consolidation improvements, or other agreed KPIs ● Performance profiling under production-scale load ● Known limitations and recommended future enhancements ● Final handover documentation and knowledge transfer session ⛳ Go/No-Go Gate: We assess results against agreed success criteria. Successful completion marks the end of the engagement, with an option to discuss ongoing support or further development. Compensation & Structure Each stage is compensated separately at an agreed rate. We prefer milestone-based billing with a not-to-exceed cap per stage (to be negotiated based on your Stage 1 estimate). Rates should reflect senior expert-level work — we are not looking for the lowest cost; we are looking for the right expertise. Please include in your proposal: ● Your proposed rate (hourly or per-stage) ● Estimated hours or cost range for Stage 1 ● Preliminary sense of total engagement cost, with the understanding that Stage 1 will produce a firmer estimate ● Availability and approximate start date All work will be considered “work for hire.” You will be required to sign a non-disclosure/non-compete agreement How to Apply Please submit a proposal that includes: ● Brief background on your relevant experience with bin packing etc., or closely related OR problems ● One or two examples of past work — describe the problem, your approach, the implementation language, and the outcome (NDA available on request for sensitive details) ● Your view on the most appropriate algorithmic approach for this class of problem, and why ● Any questions you have for us before Stage 1 begins ● Your rate and availability Proposals that engage with the technical substance of the problem will be prioritized over generic responses. We expect to conduct a short technical interview with shortlisted candidates before awarding Stage 1.