Purpose

This paper aims to focus on a medical goods distribution problem and pharmacological waste collection by plug-in hybrid vehicles with some real-world restrictions. In this research, considering alternative energy sources and simultaneous pickup and delivery led to a decrease in greenhouse gas emissions and distribution costs, respectively.

Design/methodology/approach

Here, this problem has been modeled as mixed-integer linear programming with the traveling and energy consumption costs objective function. The GAMS was used for model-solving in small-size instances. Because the problem in this research is an NP-hard problem and solving real-size problems in a reasonable time is impossible, in this study, the artificial bee colony algorithm is used.

Findings

Then, the algorithm results are compared with a simulated annealing algorithm that recently was proposed in the literature. Finally, the results obtained from the exact solution and metaheuristic algorithms are compared, analyzed and reported. The results showed that the artificial bee colony algorithm has a good performance.

Originality/value

In this paper, medical goods distribution with pharmacological waste collection is studied. The paper was focused on plug-in hybrid vehicles with simultaneous pickup and delivery. The problem was modeled with environmental criteria. The traveling and energy consumption costs are considered as an objective function.

中文翻译：

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考虑环境标准的混合动力车辆医疗物资配送和药物废物收集的人工蜂群算法

目的

本文旨在重点研究具有一些现实限制的插电式混合动力汽车的医疗物资分配问题和药物废物收集问题。在这项研究中，考虑替代能源和同时取货和送货分别导致温室气体排放和配送成本下降。

设计/方法论/途径

在这里，这个问题被建模为具有旅行和能源消耗成本目标函数的混合整数线性规划。GAMS 用于小规模实例中的模型求解。由于本研究中的问题是一个NP难问题，并且在合理的时间内解决实际大小的问题是不可能的，因此在本研究中使用人工蜂群算法。

发现

然后，将算法结果与最近文献中提出的模拟退火算法进行比较。最后，对精确解和元启发式算法获得的结果进行比较、分析和报告。结果表明，人工蜂群算法具有良好的性能。

原创性/价值

本文研究了药物废物收集的医疗物资分配。该论文的重点是同时提货和送货的插电式混合动力汽车。该问题是根据环境标准进行建模的。旅行和能源消耗成本被视为目标函数。