Nikzamir Mohammad, Baradaran Vahid
Department of Industrial Engineering, Faculty of Engineering, Islamic Azad University, Tehran North Branch, Tehran, Iran.
Transp Res E Logist Transp Rev. 2020 Oct;142:102060. doi: 10.1016/j.tre.2020.102060. Epub 2020 Aug 25.
This paper presents a novel healthcare waste location-routing problem by concentrating on a new perspective in healthcare logistics networks. In this problem, there are healthcare, treatment, and disposal centers. Locations of healthcare centers are known, however, it is required to select appropriate locations for treatment, recycling, and disposal centers. Healthcare wastes are divided into infectious and non-infectious wastes. Since a great volume of healthcare wastes are infectious, the emission of contamination can have obnoxious impacts on the environment. The proposed problem considers a stochastic essence for the emission of contamination which depends on the transferring times. In this respect, transferring times between healthcare and treatment centers have been considered as normal random variables. As transferring time increases, it is more likely for the contamination to spread. Having visited a treatment center, infectious wastes are sterilized and they will no longer be harmful to the environment. This research develops a bi-objective mixed-integer mathematical formulation to tackle this problem. The objectives of this model are minimization of total costs and emission of contamination, simultaneously. Complexity of the proposed problem led the researchers to another contribution. This study also develops a Multi-Objective Water-Flow like Algorithm (MOWFA), which is a -heuristic, to solve the problem. This algorithm uses a procedure based on the Analytical Hierarchy Process (AHP) to rank the non-dominated solutions in the archive set. By means of a developed mating operator, the MOWFA utilizes the best ranked solutions of the archive in order to obtain high quality offspring. Two neighborhood operators have been designed for the MOWFA as the local search methods. Extensive computational experiments have been conducted to evaluate the effectiveness of the MOWFA on several test problems compared with other -heuristics, namely the Multi-Objective Imperialist Competitive Algorithm (MOICA) and Multi-Objective Simulated Annealing (MOSA). These experiments also include a real healthcare waste logistic network in Iran. The computational experiments demonstrate that our proposed algorithm prevails these algorithms in terms of some well-known performance evaluation measures.
本文通过关注医疗物流网络中的一个新视角，提出了一个新颖的医疗废物定位-路径规划问题。在这个问题中，存在医疗中心、处理中心和处置中心。医疗中心的位置是已知的，然而，需要为处理、回收和处置中心选择合适的位置。医疗废物分为传染性废物和非传染性废物。由于大量医疗废物具有传染性，污染物的排放会对环境产生有害影响。所提出的问题考虑了污染物排放的随机本质，这取决于运输次数。在这方面，医疗中心和处理中心之间的运输次数被视为正态随机变量。随着运输时间的增加，污染物扩散的可能性更大。在访问处理中心后，传染性废物会进行消毒，不再对环境有害。本研究开发了一个双目标混合整数数学模型来解决这个问题。该模型的目标是同时最小化总成本和污染物排放。所提出问题的复杂性促使研究人员做出了另一项贡献。本研究还开发了一种类似多目标水流的算法（MOWFA），这是一种启发式算法，用于解决该问题。该算法使用基于层次分析法（AHP）的程序对存档集中的非支配解进行排序。通过一个开发的交配算子，MOWFA利用存档中排名最佳的解来获得高质量的后代。为MOWFA设计了两个邻域算子作为局部搜索方法。进行了广泛的计算实验，以评估MOWFA与其他启发式算法（即多目标帝国主义竞争算法（MOICA）和多目标模拟退火算法（MOSA））相比在几个测试问题上的有效性。这些实验还包括伊朗的一个实际医疗废物物流网络。计算实验表明，我们提出的算法在一些著名的性能评估指标方面优于这些算法。
