Optimizing triple bottom-line objectives for sustainable health-care waste collection and routing by a self-adaptive evolutionary algorithm: A case study from tehran province in Iran Seyed Farid Ghannadpour * , Fatemeh Zandieh , Faraneh Esmaeili Department of Industrial Engineering, Iran University of Science and Technology,16846-13114, Iran article info Article history: Received 31 December 2019 Received in revised form 4 November 2020 Accepted 5 November 2020 Available online xxx Handling Editor: Cecilia Maria Villas B^ oas de Almeida Keywords: Health-care waste collection vehicle routing problem Sustainability Risk Fuel consumption Multi objective self-adaptive evolutionary algorithm abstract The methods to collect and transport various types of medical waste are vital to the management of healthcare waste. The lack of a safe plan for the timely collection and transportation of such wastes may have an undesirable impact on the environment and public health. The present research addresses a real- life healthcare waste collection vehicle routing problem (HWCVRP) for small medical centers in Iran that produce minor amounts of waste and lack on-site facilities to treat wastes of various kinds. This problem involves social, environmental, and economic objective functions, aiming to achieve sustainable devel- opment. The social objective function is optimized based on a novel definition of risk in medical waste collection and designed to reduce public health risk by minimizing the time of waste collection from centers that produce a larger volume of more hazardous waste. Furthermore, the present paper provides a comprehensive estimate of fuel consumption in vehicles to be accurately minimized to diminish the environmental hazards involved in sustainable transportation. Also, the economic objective function is set to minimize the variable and fixed costs of transportation. A self-adaptive multi-objective evolu- tionary algorithm is generated with numerous effective operators to solve the model. Specific metrics are employed to compare the performance of the proposed meta-heuristic algorithm with those of multiple other evolutionary algorithms. The results reveal the effectiveness of the proposed method in reaching high-quality non-dominated solutions. Ultimately, a real-life case study is used to implement the pro- posed approach and to evaluate its performance. © 2020 Elsevier Ltd. All rights reserved. 1. Introduction The number of health care centers (e.g., hospitals, clinics, medical research institutes, pharmacies, private medical centers, mortuaries, and blood banks) and the services they are providing are growing each day due to the population growth and scientific advancements. Wastes generated by these healthcare centers, named healthcare wastes or medical wastes, are very diverse and hazardous. Therefore, it is essential to manage medical waste properly to avoid environmental and health risks; otherwise, environmental pollution and growth of insects are almost inevi- table that may lead to transmission of diseases (e.g., AIDS, hepatitis, etc.) to people (Hachicha et al., 2014). Different types of wastes produced in medical centers include infectious, pathological, chemical, sharps, and radioactive wastes. Health-care waste management differs from country to country. For instance, in Iran, major medical waste producers (hospitals) use on- site treatment facilities for converting their hazardous waste into non-hazardous form. Also, they are responsible for transporting their own wastes to a proper disposal facility (landfill). However, minor medical waste producers and many geographically dispersed clinics without any on-site treatment facilities can use off-site fa- cilities for treating their hazardous wastes. Therefore, a privatized contractor company is required with the capability of providing collection services and transporting their wastes to the treatment facility. In most small medical centers, there is no special restricted access area for the wastes before being collected and transported If health-care waste is not collected, managed, and disposed of properly and timely, it can pose various risks such as diseases, in- fections, and vulnerabilities (He et al., 2016; Korkut, 2018), * Corresponding author. Department of Industrial Engineering, Iran University of Science and Technology, Tehran, 16846-13114, Iran. E-mail addresses: ghannadpour@iust.ac.ir (S.F. Ghannadpour), fatemeh_ zandiyeh@ind.iust.ac.ir (F. Zandieh), esmaeili_f@ind.iust.ac.ir (F. Esmaeili). Contents lists available at ScienceDirect Journal of Cleaner Production journal homepage: www.elsevier.com/locate/jclepro https://doi.org/10.1016/j.jclepro.2020.125010 0959-6526/© 2020 Elsevier Ltd. All rights reserved. Journal of Cleaner Production xxx (xxxx) xxx Please cite this article as: S.F. Ghannadpour, F. Zandieh and F. Esmaeili, Optimizing triple bottom-line objectives for sustainable health-care waste collection and routing by a self-adaptive evolutionary algorithm: A case study from tehran province in Iran, Journal of Cleaner Production, https://doi.org/10.1016/j.jclepro.2020.125010