Research on the Integration and Scheduling of AGVs and Machines in Sample Testing Laboratory

In this paper, the problem of integration and scheduling automated guided vehicles (AGVs) inspection machines in medical sample-testing laboratories is addressed with objective minimizing maximum turnaround time (TAT). A genetic algorithm (GA) a sliding window (STW) heuristic (GA-STW) proposed for studied while incorporating vehicle assignment (VAA) decoding operations. mathematical model AGV machine established, dual-coding method process used to solve model. VAA was assign suitable AGVs each transportation task during stage. The STW further optimize initial solution allocate samples appropriate shortest AGVs. crossover operators, mutation elite numbers were experimentally optimized. numerical simulation standard examples demonstrated superiority algorithm.