基于启发式算法的生物机器人成本优化问题

Cost Optimization Problem of Biorobot Based on Heuristic Algorithm

随着微机电科技的发展,血管机器人被研发出来用于携带药物放入血管里定点治疗与血管有关的疾病,还可以充当血管清道夫,清除病毒,保持人体健康。因而血管机器人的研究和发展越来越受到人们的关注。本研究结合启发式贪心算法与粒子群算法,以血管机器人购买和保养成本为目标函数,考虑实际每周血管机器人需求数量,提出约束条件,建立机器人购买优化模型。结果显示,结合贪心算法和粒子群算法相比于传统求解寻优能力有了较高的提升,效率更高,结果更准确,适用于血管机器人成本优化问题。

With the development of micro-electromechanical technology, vascular robots have been developed to carry drugs into blood vessels to treat vascular-related diseases. They can also act as vascular scavengers, remove viruses, and maintain human health. Therefore, the research and development of vascular robots have attracted more and more attention. This study combines heuristic greedy algorithm and particle swarm optimization algorithm, takes the purchase and maintenance cost of vascular robots as the objective function, considers the actual weekly demand for vascular robots, proposes constraints, and establishes a robot purchase optimization model. The results show that the combination of greedy algorithm and particle swarm optimization algorithm has a higher improvement than the traditional solution optimization ability, higher efficiency, more accurate results, and is suitable for the cost optimization problem of vascular robots.