Operations Research & Cargo Optimization
Making high-stakes allocation and operational decisions under real constraints.
The challenge.
A collection of applied decision-science capabilities including cargo allocation, loading and discharge sequencing, stability-aware planning, and cargo heating strategy optimization. Focused on deployable models rather than purely academic formulations.
Why this matters.
Cargo planning requires balancing commercial and operational objectives while respecting constraints such as vessel stability, loading/discharge sequence, cargo compatibility and available capacity. Cargo heating introduces a related but distinct decision problem involving temperature requirements and energy use.
I have worked on Operations Research applications that turn these competing considerations into practical decision-support capabilities for maritime operations. The same optimization mindset is transferable to scheduling, industrial resource allocation and energy planning.
From idea to working system.
Applied mathematical optimization and decision-support engineering using tools such as AMPL and Google OR-Tools. The portfolio covers cargo allocation and sequencing, alongside cargo-heating optimization as an application area.
The emphasis is not simply finding a theoretical best answer; it is giving planners feasible, explainable options that can be used within operational workflows.
Practical applications.
Allocation decisions informed by vessel constraints
Support for loading and discharge planning
Energy-aware cargo-heating decision support
Reusable optimization thinking across industries
Engineering highlights.
Cargo allocation and discharge-sequencing decision support
Cargo heating as an energy-and-constraint optimization application
Bridging mathematical models with operational tools
Technical capabilities.
What it enables.
More consistent planning decisions
Resource and energy decision support
Operational constraint awareness
Descriptions are high-level capability summaries. Client-specific designs, sensitive data, source code and proprietary implementation details are intentionally omitted.
Have a similar challenge?
I can help clarify the problem, choose a practical engineering approach and build toward a usable outcome.
Let's talk ↗Related work.
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