Simultaneously Solving Computational Problems Using an Artificial Chemical Reactor

TL;DR

This paper introduces an artificial chemical reactor that uses chemical reaction metaphors to solve multiple unrelated problems simultaneously, demonstrating effectiveness in genomic, routing, and scheduling tasks.

Contribution

It presents a novel distributed stochastic algorithm that models a chemical universe to solve diverse problems concurrently, a significant advancement over traditional single-problem approaches.

Findings

Successfully solved genomic similarity problems with quality solutions.

Effectively optimized Hamiltonian cycles for the traveling salesman problem.

Improved aircraft landing schedules by minimizing penalty costs.

Abstract

This paper is centered on using chemical reaction as a computational metaphor for simultaneously solving problems. An artificial chemical reactor that can simultaneously solve instances of three unrelated problems was created. The reactor is a distributed stochastic algorithm that simulates a chemical universe wherein the molecular species are being represented either by a human genomic contig panel, a Hamiltonian cycle, or an aircraft landing schedule. The chemical universe is governed by reactions that can alter genomic sequences, re-order Hamiltonian cycles, or reschedule an aircraft landing program. Molecular masses were considered as measures of goodness of solutions, and represented radiation hybrid (RH) vector similarities, costs of Hamiltonian cycles, and penalty costs for landing an aircraft before and after target landing times. This method, tested by solving in tandem with deterministic algorithms, has been shown to find quality solutions in finding the minima RH vector similarities of genomic data, minima costs in Hamiltonian cycles of the traveling salesman, and minima costs for landing aircrafts before or after target landing times.