This paper investigates a vehicle routing problem arising in the waste collection of the healthcare system with the concern of transportation risk. Three types of facilities abstracted from the health system are investigated in this paper, namely, facilities with collection points, facilities without collection points, and small facilities. Two-echelon collection mode is applied in which the waste generated by small facilities is first collected by collection points, and then transferred to the recycling centre. To solve this problem, we propose a mixed-integer linear programming model considering time windows and vehicle capacity, and we use particle swarm optimisation (PSO) algorithm for solving large-scale problems. Numerical experiments show the capability of the proposed algorithm. Sensitivity analysis is conducted to investigate the influence of facilities with collection points and the collection routes. This research can provide a decision support tool for the routing of waste collection in the healthcare system.
The dramatic increase in medical waste has put a severe strain on sorting operations. Traditional manual order picking is extremely susceptible to infection spread among workers and picking errors, while automated medical waste sorting systems can handle large volumes of medical waste efficiently and reliably. This paper investigates the optimization problem in the automated medical waste sorting system by considering the operational flow of medical waste. For this purpose, a mixed-integer programming model is developed to optimize the assignment among medical waste, presorting stations, and AGVs. An effective variable neighborhood search based on dynamic programming algorithm is proposed, and extensive numerical experiments are conducted. It is found that the proposed algorithm can efficiently solve the optimization problem, and the sensitivity analysis gives recommendations for the speed setting of the conveyor.
To study the efficacy of rapamycin (RAPA)-chitosan (CS)-calcium alginate (CA) sustained-release microspheres on scar formation in a rabbit model of glaucoma filtration surgery. Eighty New Zealand white rabbits were randomly divided into four groups and a glaucoma filtration model was established by scleral bite through the eyes. RAPA-CS-CA sustained-release microspheres were implanted in the right eye of 40 rabbits (Group A) and CS blank sustained-release microspheres were implanted in the left eye (Group B). Another 40 rabbits were treated with a 0.2 g·L-1 RAPA cotton sheet in the right eye (Group C) and the left eye underwent a simple sclerotomy (Group D). The intraocular pressure, filter bleb, anterior chamber inflammation, complications, and corneal endothelial cell density were observed after the operation. Rabbits were euthanized for pathological examination 7 days, 14 days, and 21 days after the operation. The drug loading rate of RAPA-CS-CA sustainedrelease microspheres was (34.58±1.47)% and the encapsulation rate was (56.23±1.55)%. The microsphere release in vitro was relatively stable. The release rate of the microspheres during the burst was only 16.54%. After 49 days, the cumulative release rate of the microspheres reached 94.07% and the sustained release effect was significant within 45 days. Group A maintained low-level intraocular pressure for the longest period of time, followed by Group C, and then Group B and D. The survival time of filter vesicles in Group A was longer than that in other groups. There were no postoperative complications in each group. The conjunctival epithelium of Group A had better integrity and fewer subconjunctival fibroblasts than other groups. There was no obvious inflammation or infiltration around the filtering mouth and there were fewer new collagen fibers. RAPA-CS-CA slow-release microspheres safely and effectively inhibited the proliferation of fibroblasts and neonatal collagen fibers in rabbit glaucoma filtration surgery and significantly improved the success rate of glaucoma filtration surgery.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.