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 meta-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 meta-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.

本文着重于医疗物流网络中的新观点，提出了一个新颖的医疗废物选址路由问题。在这个问题上，有医疗保健，治疗和处置中心。医疗中心的位置是已知的，但是，需要选择适当的位置进行处理，回收和处置。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，因此污染物的排放可能对环境产生有害影响。提出的问题考虑了取决于排放时间的污染物排放的随机本质。在这方面，医疗和治疗中心之间的转移时间已被视为正常的随机变量。随着传输时间的增加，污染物更可能扩散。参观过治疗中心后，传染性废物已得到消毒，它们将不再对环境有害。本研究开发了一种双目标混合整数数学公式来解决此问题。该模型的目标是同时最大程度地降低总成本和污染物排放。所提出问题的复杂性使研究人员做出了另一贡献。本研究还开发了一种多目标水样算法（MOWFA），该算法 该模型的目标是同时最大程度地降低总成本和污染排放。所提出问题的复杂性使研究人员做出了另一贡献。本研究还开发了一种多目标水样算法（MOWFA），该算法 该模型的目标是同时最大程度地降低总成本和污染物排放。所提出问题的复杂性使研究人员做出了另一贡献。本研究还开发了一种多目标水样算法（MOWFA），该算法元启发式，以解决问题。该算法使用基于层次分析过程（AHP）的过程对归档集中的非主导解决方案进行排名。通过发展成熟的交配者，MOWFA利用档案馆中排名最高的解决方案来获得高质量的后代。已经为MOWFA设计了两个邻域运算符作为本地搜索方法。已经进行了广泛的计算实验，以评估MOWFA与其他元数据相比在一些测试问题上的有效性。-启发式，即多目标帝国主义竞争算法（MOICA）和多目标模拟退火（MOSA）。这些实验还包括伊朗的一个真正的医疗废物物流网络。计算实验表明，本文提出的算法在一些著名的性能评估指标上优于这些算法。