# A Path-Driven Fluid Routing and Scheduling Method for Continuous-Flow Microfluidic Biochips with Delay Time Optimization

## TL;DR

This paper introduces a new method for designing microfluidic biochips that improves efficiency by combining routing and scheduling.

## Contribution

The paper presents an integrated path-driven approach that jointly optimizes routing and application mapping for microfluidic biochips.

## Key findings

- The method reduces total channel length by 22.05% compared to existing techniques.
- It also decreases total delay time by 21.97% and biochemical reaction completion time by 8.30%.

## Abstract

Routing and application mapping are critical stages in the design of continuous-flow microfluidic biochips (CFMBs). The routing stage determines the channel network connecting components and ports, while application mapping schedules fluid transportation and wash operations based on the designed biochip architecture. Existing methods typically handle these stages separately: routing focuses solely on physical metrics without considering subsequent scheduling requirements, while application mapping adopts one-shot scheduling strategies that can lead to suboptimal solutions. This paper proposes an integrated path-driven methodology that jointly optimizes routing and application mapping. For routing, we develop a hybrid particle swarm optimization algorithm that incorporates conflict awareness and channel utilization strategies. For application mapping, we introduce an iterative approach that leverages historical scheduling information to progressively optimize fluidic-handling and wash operations. Experimental results on both real and synthetic benchmarks demonstrate significant improvements over state-of-the-art methods, achieving reductions of 22.05% in total channel length, 21.79% in intersections, 21.97% in total delay time, and 8.30% in biochemical reaction completion time. The proposed methodology provides an effective solution for the automated design of CFMBs with enhanced physical and operational efficiency.