Modeling transfer station locations considering source separation of solid waste in urban centers: A case study of Bilaspur city, India

Rathore, Pradeep; Sarmah, S.P.

doi:10.1016/j.jclepro.2018.11.100

Cited by 75 publications

(32 citation statements)

References 29 publications

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“…Waste management may be a daily task in metropolitan zones involving arranging waste truck routes in which natural, monetary, and social elements must be considered. Secondly, the length needs to be abbreviated to maintain a strategic distance from high fuel costs and diminish the work sum by applying the diagram hypothesis [8]. A couple of arrangements have presented IoT gadgets to appraise inboxes' fill levels and send this information over the web for better decisions.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Machine Learning and IoT‐Based Waste Management Model

Khan

Kumar

Srivastava³

et al. 2021

Computational Intelligence and Neuroscience

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A rapid rise in inhabitants across the globe has led to the inadmissible management of waste in various countries, giving rise to various health issues and environmental pollution. The waste-collecting trucks collect waste just once or twice in seven days. Due to improper waste collection practices, the waste in the dustbin is spread on the streets. Thus, to defeat this situation, an efficient solution for smart and effective waste management using machine learning (ML) and the Internet of Things (IoT) is proposed in this paper. In the proposed solution, the authors have used an Arduino UNO microcontroller, ultrasonic sensor, and moisture sensor. Using image processing, one can measure the waste index of a particular dumping ground. A hardware prototype is also developed for the proposed framework. Thus, the presented solution for the efficient management of waste accomplishes the aim of establishing clean and pollution-free cities.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Machine Learning and IoT‐Based Waste Management Model

Khan

Kumar

Srivastava³

et al. 2021

Computational Intelligence and Neuroscience

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“…Inappropriate and inadequate MSWM increases the difficulties concerning MSW facilities' location regarding public opposition, land cost, and a lack of adequate land. Within the ISWM system, transfer stations (TSs) emerge, as a sustainable alternative, to optimize the collection-transportation phase, representing between 50 and 70% of the global cost (Rathore & Sarmah, 2019). A TS is a technically established place to allow non-hazardous MSW discharge and temporary storage before the transportation to the final disposal sites (FDSs) (Eiselt & Marianov, 2015;.…”

Section: Introductionmentioning

confidence: 99%

“…More volumetric capacity vehicles, appropriate for travelling long distances, are used. Hussain et al (2014), Li and Huang (2010), and Yong et al (2009) agree that direct transportation is not always appropriate because FDSs are distant from populated areas to prioritize public health (Rathore & Sarmah, 2019). Using TSs presents four advantages: (1) Optimization and efficiency of collection trucks, which results in collection coverage growth.…”

Section: Introductionmentioning

confidence: 99%

“…( 4) Transportation efficiency by reducing the number of trips to FDSs by using more capacity trucks to cover the route from TSs to FDSs (Bosompem et al, 2016). Thereby, TSs are economically viable and will reduce the collection cost by around 30% (Rathore & Sarmah, 2019). In developing countries, Chile has experienced a reduction of 33.3% (Vásquez, 2005), while Indian a 25% (Paul et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Suitable site selection for transfer stations in a solid waste management system using analytical hierarchy process as a multi-criteria decision analysis: a case study in Azuay-Ecuador

Mora

Guamán-Aucapiña

Zúñiga-Ruiz

2022

Environ Dev Sustain

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To guarantee a dignified life in low-incoming countries where socio-environmental negative implications derived from the municipal solid waste (MSW) by its excessive generation, lack of governance, and financial resources, sustainable and integrated solutions are required. From this perspective, well-located transfer stations (TSs) are conceived as an alternative to improve MSW management quality in municipalities that generate little MSW and have long transportation distances. Consequently, this research aims to find optimum areas to locate TSs in the province of Azuay-Ecuador as a commonwealth proposal. It applies a multi-criteria decision analysis based on geographic information systems with the analytical hierarchical process technique: a heuristic and scalable method that simultaneously evaluates subjective and non-monetized inputs. The authors faced it from a holistic perspective in a three-level hierarchical structure; starting from categories: technical, environmental, economic, and social; then criteria: rivers, protected areas, populated areas, land use, educational centers, health centers, tourist sites, basic services, roads, gravity centers, geology, power grid, and slopes; and finally, sub-criteria defined by criteria´s measurable attributes. This research provides local decision-makers with middle-scale tools and a first diagnosis to focus later efforts in local studios over potential sites. The results showed that 79.12% of the study area was restrictive to place a TS. The remaining territory suitability index values between 13 and 89% were found, with possible TSs at Paute, Sigsig, and Nabón to serve nine from fifteen cantons.

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“…For instance, in a similar fashion to FLP, one study [5] reported an approach for selecting construction materials in an engineering design project. An extensive range of models exists in the literature for describing practical problems of optimization involving service point locations in waste management, and some of these mathematical formulations are discussed in this study (see [6][7][8][9][10][11][12][13][14][15][16][17][18] for examples). The differences and similarities in these models are discussed more succinctly under the application section as many of them find direct applications in solid waste management where municipal authorities are often confronted with the enormous challenge of locating waste collection facilities as well as landfills within their municipalities because of limited financial resources.…”

Section: Introductionmentioning

confidence: 99%

Facility Location Problems: Models, Techniques, and Applications in Waste Management

Adeleke

Olukanni

2020

Recycling

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This paper presents a brief description of some existing models of facility location problems (FLPs) in solid waste management. The study provides salient information on commonly used distance functions in location models along with their corresponding mathematical formulation. Some of the optimization techniques that have been applied to location problems are also presented along with an appropriate pseudocode algorithm for their implementation. Concerning the models and solution techniques, the survey concludes by summarizing some recent studies on the applications of FLPs to waste collection and disposal. It is expected that this paper will contribute in no small measure to an integrated solid waste management system with specific emphasis on issues associated with waste collection, thereby boosting the drive for effective and efficient waste collection systems. The content will also provide early career researchers with some necessary starting information required to formulate and solve problems relating to FLP.

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Modeling transfer station locations considering source separation of solid waste in urban centers: A case study of Bilaspur city, India

Cited by 75 publications

References 29 publications

[Retracted] Machine Learning and IoT‐Based Waste Management Model

[Retracted] Machine Learning and IoT‐Based Waste Management Model

Suitable site selection for transfer stations in a solid waste management system using analytical hierarchy process as a multi-criteria decision analysis: a case study in Azuay-Ecuador

Facility Location Problems: Models, Techniques, and Applications in Waste Management

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