Are Near Earth Objects the Key to Optimization Theory?

TL;DR

This paper explores the analogy between near earth objects and Central Force Optimization, proposing that NEO theory could provide solutions to key challenges in deterministic optimization such as local trapping and convergence proof.

Contribution

It introduces a novel connection between NEO theory and CFO, suggesting that insights from NEO dynamics may improve optimization algorithms.

Findings

CFO's Davg exhibits oscillatory plateau regions similar to NEO Delta-V curves.

The analogy suggests CFO's gravity metaphor may help address local trapping.

Potential for NEO theory to enhance convergence proofs in optimization.

Abstract

This note suggests that near earth objects and Central Force Optimization have something in common, that NEO theory may hold the key to solving some vexing problems in deterministic optimization: local trapping and proof of convergence. CFO analogizes Newton's laws to locate the global maxima of a function. The NEO-CFO nexus is the striking similarity between CFO's Davg and an NEO's Delta-V curves. Both exhibit oscillatory plateau-like regions connected by jumps, suggesting that CFO's metaphorical "gravity" indeed behaves like real gravity, thereby connecting NEOs and CFO and being the basis for speculating that NEO theory may address difficult issues in optimization.