{"title":"A Multi-Objective Periodic Vehicle Routing Model for Sustainable Healthcare Waste Collection.","authors":"Hajer Ben-Romdhane","doi":"10.1002/hpm.70112","DOIUrl":null,"url":null,"abstract":"<p><p>The collection of infectious waste from healthcare facilities (HCF) constitutes a recurring operational challenge. Indeed, despite the inherent health risks posed by the storage and the transportation of infectious materials, most of the existing waste collection systems tends to prioritise cost optimization and to underaddress the safety dimension. Besides, the collection frequency must be tailored to the waste generation rate of each healthcare facility to avoid delays and inefficiencies. Therefore, it is clear that finding the best collection schedule that guarantees safety within HCF, transportation security, and economic profits is both critical and difficult to achieve. In order to more accurately model the described problem, this study introduces the Sustainable and Load-dependent Periodic Vehicle Routing Problem (S-PVRP). The proposed model aims to optimises three objectives: the travelled distance, the transportation risk and the storage risk. Besides, it is designed in a such a way to trigger the collection when a threshold value is reached. To solve the S-PVRP, we design two solution approaches with very well selected ingredients in order to strike a balance between the exploration and exploitation aspects by reasoning upon multiple objectives. An experimental study is carried out to prove the efficiency of the algorithm on multi-objective optimization. The algorithm is tested on several benchmark instances and evaluated via several performance metrics. Indeed, we have compared the performance of our algorithm against state-of-the-art algorithms. The experimental results showed that the proposed approach MX-GAOPT is very competitive and outperforms the competing algorithms in most cases.</p>","PeriodicalId":47637,"journal":{"name":"International Journal of Health Planning and Management","volume":" ","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2026-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Health Planning and Management","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/hpm.70112","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH POLICY & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
The collection of infectious waste from healthcare facilities (HCF) constitutes a recurring operational challenge. Indeed, despite the inherent health risks posed by the storage and the transportation of infectious materials, most of the existing waste collection systems tends to prioritise cost optimization and to underaddress the safety dimension. Besides, the collection frequency must be tailored to the waste generation rate of each healthcare facility to avoid delays and inefficiencies. Therefore, it is clear that finding the best collection schedule that guarantees safety within HCF, transportation security, and economic profits is both critical and difficult to achieve. In order to more accurately model the described problem, this study introduces the Sustainable and Load-dependent Periodic Vehicle Routing Problem (S-PVRP). The proposed model aims to optimises three objectives: the travelled distance, the transportation risk and the storage risk. Besides, it is designed in a such a way to trigger the collection when a threshold value is reached. To solve the S-PVRP, we design two solution approaches with very well selected ingredients in order to strike a balance between the exploration and exploitation aspects by reasoning upon multiple objectives. An experimental study is carried out to prove the efficiency of the algorithm on multi-objective optimization. The algorithm is tested on several benchmark instances and evaluated via several performance metrics. Indeed, we have compared the performance of our algorithm against state-of-the-art algorithms. The experimental results showed that the proposed approach MX-GAOPT is very competitive and outperforms the competing algorithms in most cases.
期刊介绍:
Policy making and implementation, planning and management are widely recognized as central to effective health systems and services and to better health. Globalization, and the economic circumstances facing groups of countries worldwide, meanwhile present a great challenge for health planning and management. The aim of this quarterly journal is to offer a forum for publications which direct attention to major issues in health policy, planning and management. The intention is to maintain a balance between theory and practice, from a variety of disciplines, fields and perspectives. The Journal is explicitly international and multidisciplinary in scope and appeal: articles about policy, planning and management in countries at various stages of political, social, cultural and economic development are welcomed, as are those directed at the different levels (national, regional, local) of the health sector. Manuscripts are invited from a spectrum of different disciplines e.g., (the social sciences, management and medicine) as long as they advance our knowledge and understanding of the health sector. The Journal is therefore global, and eclectic.