You may search for an nature inspired optimization algorithm or a recent swarm intelligence based optimization algorithm and try improving it. Following steps might be helpful when creating a variant of an existing algorithm:
1. Understand the target algorithm thoroughly. understand the base paper, try reproducing results reported in the original paper.
2. Literature Review: Look at the available variants of the target algorithm as well as others work on "How to improve an optimization algorithm", you may consider variants of PSO or WOA or GWO, these are mature algorithms with a lot of existing variants.
3. Brainstorm modification: it is time to finalize modification for your chosen algorithm.
4. Define a clear Hypothesis: Formulate a clear hypothesis about how your modifications will lead to an improvement in the algorithm's performance. Your hypothesis should be testable and measurable.
5. Implementation: Easiest way is to use matlab, many codes are available online and many tutorials on how to program in matlab. You may use python as well.
6. Test on the common benchmark functions
7. Compare and Analyze results.
8. Iterate and refine: Refine the algorithm based on the testing and comparison.
You may design and make a sofware in order to help tecnicians involve in PM or an app to calculate the demands of materials in factory based on BOM (you must design for a simple production).
Have you considered developing a solution that evaluates wealth transfer factors across countries and cultures and uses that learning to project pro forma impacts of economic policy changes? That is, 1. What factors lead to wealth transfer within a society, 2. If those factors continue unchanged, what wealth transfer can be expected for impacted stakeholders, and 3. What would be the impact on wealth transfer in a society, if certain factors or combinations were changed?
If u going to use python go for image segmentation. If u going to use java go for intrepreter speed or accuracy improvement. If .net go for malware detection