I’m in the middle of an academic project that explores new ways to design combinatorial optimisation algorithms with the single-minded aim of boosting accuracy. At this stage I have initial ideas and some preliminary notes, but I want to turn the work into one or more publication-ready papers that can stand up to peer review. Here’s what I need from you: • Refine and formalise the core algorithmic idea, making sure the design choices are clearly justified and theoretically sound. • Compare the proposed approach against the current state of the art; a tight, up-to-date literature review is essential. • Develop or help polish experiments (Java or a similar numerical stack) that demonstrate superior solution quality gains on representative optimisation problems that outperform the state of the art. • Shape the full manuscript in LaTeX—from abstract through conclusions—ensuring the writing is clear, persuasive and consistent with target journal guidelines. The problem I am working on is the home healthcare routing and scheduling problem with interdependent services. I am currently using genetic algorithms, and potentially considering reinforcement learning. I’m happy to share existing notes, datasets and preliminary code the moment we agree on scope. If you’ve published optimisation or meta-heuristic research before and are comfortable backing claims with solid statistical analysis, you’ll be a great fit. Let’s discuss milestones so we can move efficiently from concept to submission. ------------------------------------------------------------------------------- The project involves refining and formalizing your core algorithmic idea, ensuring sound design choices and theoretical backing. It includes comparing the approach against the state of the art with an updated literature review, developing or polishing experiments (likely in Java or similar) to showcase superior performance on representative optimization problems, and drafting a publication-ready manuscript in LaTeX. The focus is achieving preliminary results, detailed algorithm design, implementation code, and a draft publication within 7 days.