Waste Collection Company Research Articles

A rolling horizon heuristic approach for a multi-stage stochastic waste collection problem

In this paper we present a multi-stage stochastic optimization model to solve an inventory routing problem for the collection of recyclable municipal waste. The objective is the maximization of the total expected profit of the waste collection company. The decisions are related to the selection of the bins to be visited and the corresponding routing plan in a predefined time horizon. Stochasticity in waste accumulation is modeled through scenario trees generated via conditional density estimation and dynamic stochastic approximation techniques. The proposed formulation is solved through a rolling horizon approach, providing a rigorous worst-case analysis on its performance. Extensive computational experiments are carried out on small- and large-sized instances based on real data provided by a large Portuguese waste collection company. The impact of stochasticity on waste generation is examined through stochastic measures, showing the importance of adopting a stochastic model over a deterministic formulation when addressing a waste collection problem. The performance of the rolling horizon approach is evaluated, demonstrating that this heuristic provides cost-effective solutions in short computational time. Managerial insights related to different geographical configurations of the instances and varying levels of uncertainty are finally discussed.

Assessing the circularity status of waste management among manufacturing, waste management, and recycling companies in Kigali, Rwanda

A high quantity of waste is generated from industrial activities by manufacturers across metropolitan cities compared to smaller cities with fewer industrial activities. Adopting Circular Economy principles in waste management has the potential for sustainable waste management to reduce the quantity of waste at dumpsites and harmful emissions from wastes. The study was conducted to assess circularity status and challenges for attaining higher circularity by Kigali’s manufacturing, waste collection, and waste recycling companies using the 10-R framework. The study also sought to build estimates for industrial solid waste quantity and methane emissions for the next 10 years (2020–2030) in Rwanda. A mixed method approach was utilized where primary data was collected from manufacturing, waste collection, and waste recycling companies using a validated questionnaire and an in-depth interview guide. Thematic, descriptive analysis and First Order Decay methods were used to analyze the qualitative, quantitative, and secondary data. Results show that adopting the 10-R principles of circular economy was low and varies across manufacturing, waste collection and recycling companies. There were instances of high adoption of R3-Reuse and R8-Recycle with a mean score of 7.17 and 7.21 among manufacturing companies. R7-Repurpose (8.80) recorded a high adoption rate among waste collection companies and a medium level of adoption for R7-Repurpose (3.50) and R9-Recover (3.00) among recycling companies. The overall low adoption toward attaining circularity was attributed to various economic, institutional, infrastructural, operational, attitudinal, and technological challenges. In 2030, it is projected that 922 Gg of industrial waste will be deposited in solid waste disposal sites in Rwanda; with an estimated methane emission of 157 Gg Carbon dioxide equivalence. It was recommended among others, that human resource capacity development should be prioritized to drive the adoption of the 10-R principles across manufacturing, waste collection, and waste recycling companies in Kigali, which can reduce the quantity of wastes that ends at dumpsites and methane emissions that contribute significantly to global warming.

Waste bunker size optimization under uncertainty: Application of inventory models with real data simulation

Waste-to-Energy (WtE) technologies play a prominent role in recovering energy from waste. One of the aspects ensuring the operability and economic sustainability of WtE plants is the size optimization of a waste bunker assigned to each WtE plant, whose main target is to ensure waste homogeneity for effective operation. Each WtE plant faces various uncertain challenges, such as planned and unplanned shutdowns during which the plant is inactive and not ideally coordinated with waste collection companies, further importing the collected waste into the waste bunker, mainly due to existing contracts. This work aims to develop a scenario-based model to support strategic capacity planning by capturing various uncertain attributes and optimizing the waste bunker size while minimizing the total costs composing the investment, inventory, and waste shortage costs. The model is tested on a case study from the Czech Republic. The main result can be summarized such that for a specific case of a newly situated WtE facility with a considered capacity of 100kt/y, the model suggests a bunker of size ca. 4,200m3 for a middle scenario. However, this is strongly related to other attributes of a particular WtE project (e.g., waste properties or cost parameters).

The evaluation of energy consumption in transportation and processing of municipal waste for recovery in a waste-to-energy plant: a case study of Poland.

Refuse-derived fuel (RDF) can be produced from combustible materials contained in municipal waste. This article investigates energy and material flow of waste in different scenarios for production of RDF from bulky waste, separately collected waste, and mixed municipal solid waste (MSW). We compare the proportion of energy consumption in transportation, handling waste, and processing using data from the waste collection company in South Poland. The findings show the components of the reverse supply chain consuming the highest value of energy. A model of material and energy flow has taken into consideration collection of waste and transportation by two categories of waste collection vehicles: light commercial vehicles and garbage trucks. The shipping of RDF from pre-treatment facilities uses tipper semi-trailers and walking floor trailers. The findings of the study show production of RDF from municipal solid waste consumes almost 10% of energy potential in RDF. Less energy is required for the production of RDF from bulky waste (2.2-4.8%) or separately collected waste (1.7-4.1%) depending on the efficiency of collection and selected vehicles. Transportation consumes the greatest portion of energy. For mixed municipal solid waste (MSW), it can reach 79%; for separated collection waste, 90%; and for bulky waste, up to 92% of the total energy consumed. Comparing emissions for two categories of the collection vehicles, no significant difference was found for the bulky waste collections. For mixed MSW and separately collected waste, the emissions are higher for garbage trucks. A recommendation for practitioners is optimization of routing to achieve a higher collection rate at a minimized route length. For transportation of RDF to WtE plants, vehicles with higher loading capacity are essential.

The Effects of Subsidies on MSW Treatment Companies: Financial Performance and Policy Implications

Companies that provide public services usually receive subsidies from municipalities as compensation for replacing the latter in their functions as public service providers. However, the managers of those companies are not always interested in maintaining an economically sustainable company, as this implies turning off the tap on exploration subsidies. This article investigates the effect of subsidies on the financial performance of municipal solid waste collection and treatment companies for 2016–2020 and across NUTS II regions. The accounting data of 680 companies retrieved from the SABI database, make it possible to assess the economic sustainability of the companies through financial ratios and operational data. The results show that the financial structure and management of companies in the Centro, Lisbon, and the Azores allowed to take advantage of exploration subsidies to achieve economic sustainability. In the remaining regions these subsidies proved to be ineffective. These results have implications for managers and policy makers insofar as it sheds a light on the conditions under which subsidies contribute to the economical sustainability of companies in the sector.

Influential Factors Affecting Solid Wastes Management in Kigali City, Rwanda

The study shows some challenges that hinder effective solid waste management in Kigali City including social behavior, financial, technical, low technology factors, and limited support and subsidies which affect solid waste management. Data were collected from staff working in different waste collection companies in the city of Kigali. Eighty workers responded to the questionnaire. The interviewed people were divided into two groups, owners or managers and field workers. Workers were selected from all the 14 wastes companies operating in Kigali. The study shows that the solid waste collection has encountered many problems: no proper sorting of waste, low willingness to pay, inadequate training and awareness-raising on solid waste management, insufficient budget, low level of technology in recycling which is still at 2%, and low income for staff working in waste collection companies. Hence, the government of Rwanda must revolutionize its support of the sector and promote as system like the South Korean pay-as-you-throw model, not by merely imitating it, but by motivating the private sector to invest in recycling. The study also recommends that Nduba landfill be rehabilitated and transformed into a model landfill capable of accommodating all waste efficiently.

Sustainable solid waste management in restaurants: The case of the Ecozinha Institute, Brazil

This study aimed to propose a systematic model for the sustainable management of solid waste in restaurants, based on the experience of the Ecozinha Institute (Brazil). The Solid Waste Management System for Restaurants (SGRS-R) was developed through a case study conducted in a Brazilian restaurant. Data on meal preparation processes were collected through direct observation and recorded on forms designed specifically for this purpose according to parameters and guidelines described in the literature. Corrective actions already in place were monitored, and the need for new actions was identified. SGRS-R consists of seven steps, two of which are aimed at defining corrective actions and recommendations for solid waste management and reduction. The other five steps are supported by evaluation forms for (1) gravimetric control of solid waste, (2) description of physical infrastructure and solid waste equipment, (3) survey of solid waste collection, recycling, and disposal companies, (4) description of the flow of solid waste, and (5) monitoring of meal preparation steps. It was observed that SGRS-R implementation promoted changes in meal preparation processes in line with the principles of waste avoidance, reduction, reuse, and recycling. Waste management plans implemented by the Ecozinha Institute were able to reduce the amount of solid waste sent to sanitary landfills by up to 90%. It is important to emphasize that SGRS-R can be adapted and applied to any type of restaurant, given that solid waste management criteria are defined for each meal preparation step. SGRS-R can be used to restructure the management of solid waste in restaurants through strategies that include from menu planning to temporary storage of solid waste, thereby minimizing the environmental impacts associated with food service.

A Mathematical Model for Scheduling and Assignment of Customers in Hospital Waste Collection Routes

The collection, transport, and final disposal of hospital waste may cause contamination and disease if improperly handled. Therefore, such residues are hazardous to the health of waste collectors. These wastes are generated by public agencies, such as hospitals, family health centers, dialysis centers, and private healthcare providers. In this study, a mixed-integer linear programming model is proposed for monthly customer scheduling and route assignment. The proposed approach was fulfilled according to customers’ collection frequency, truck capacity, and customer geographical location. The proposed mathematical model successfully balanced the number of customers and the workload during each day. The effectiveness of the proposed model was tested on data obtained from a waste collection company. The model has been implemented in AMPL language, and the performance of commercial solvers, GUROBI and CPLEX, to obtain an optimal solution were tested. The results show the efficiency of the proposed approach to balance the workload concerning previous scheduling is done ad hoc at the company. The use of the formulated model provides an automatic procedure that was previously performed manually. The methodology can be adapted to other companies with similar requirements.

Collecting Small-Waste Electrical and Electronic Equipment in Poland—How Can Containers Help in Disposal of E-Waste by Individuals?

The effectiveness of e-waste collection depends on organizational and social factors. Individuals should have easy access to collection points and be aware of proper methods of e-waste disposal. This article investigates the availability, usability, and occurring irregularities of the container collection of small-waste electrical and electronic equipment. The study explores the attitude and behavior of individuals when disposing of small-waste equipment in the South of Poland. The results show that ninety-five percent of supermarkets’ managers responsible for waste management find a growing interest in the disposal of small e-waste by individuals. An increasing number of collection containers encourages residents to dispose of small-waste appliances. More than eighty-three percent of respondents are aware of proper methods of e-waste disposal. Additional information campaigns addressed to residents are required to prevent mixing electrical and electronic waste with other waste and to encourage the disposal of small e-waste. The intention to dispose of small e-waste was declared by only thirty-two percent of respondents. Containers with discarded easy breakable items, such as lamps, should be removed more frequently. The collection containers’ noticeability is evaluated by individuals as of average difficulty. The containers in supermarkets have simple designs and labels indicating the category of waste for disposal. The containers installed in residential areas have attractive designs and advertising slogans. The individuals expect the containers should be available in more locations that are easily accessible from households. The results of this study should be helpful for local authorities, waste collection companies, and waste electrical and electronic organizations, to support design, location selection, and information campaigns for small e-waste container collections.

Safety values, attitudes and behaviours in workers of a waste collection and sanitation company

The values, attitudes and safety behaviours expressed by workers are an important aspect when determining the success of a company's performance in the field of safety and health at work. The data compiled from a non-probabilistic random sample of 200 workers from a waste collection and sanitation company in northeastern Brazil played a role in portraying some of the organisation's cultural traits in terms of occupational safety and health conditions and organisational safety climate in this segment of workers. It can be concluded that the company has an overall positive safety climate, in particular how safety was considered an organisational value, and also workers’ perception about the general safety principles in the company is very positive. The only parameter that was negatively assessed concerns the quality of safety communications, presenting an opportunity for improvement. The research hypotheses formulated were only partially confirmed, yet it was possible to assess that factors such as safety training, the quality of safety communications, the control of the effects of work pace on safety, the perception of safety management values and practices in the organisation and the institutional strength of the internal safety services had a favourable bearing on determining the level of safety maturity and risk perception of workers.

The efficiency of municipal solid waste collection in Mexico.

Since the 1980's, some Mexican municipalities have subcontracted waste collection services to private companies, with an eye on increasing the efficiency of this service. However, the impact of private management on the Mexican waste sector performance has not been evaluated. In this study, the efficiency of waste collection in Mexico was analyzed to test the hypothesis that private companies are more efficient at waste collection than municipal governments. A two stage double bootstrap Data Envelopment Analysis (DEA) was applied to a sample of 1,626 municipalities. In the first stage, unbiased efficiency scores were calculated, and in the second stage, these scores were regressed against a set of environmental covariates which were thought to affect efficiency, including a dummy variable to identify the municipalities where waste is collected by a private company. Results suggest that private waste collection companies are more efficient than municipal governments. Other environmental variables such as population density, average household income, and tourism were also found to affect waste collection efficiency. The analysis also indicates that curbside collection is associated with a higher efficiency, while separate collection of waste is negatively correlated to efficiency.

Estimating Time Spent at the Waste Collection Point by A Garbage Truck with A Multiple Regression Model

The planning of the garbage trucks’ routes is an essential process in waste collection companies. The main issues in garbage truck routing are determining the optimal routes, minimizing time, decreasing the costs, and reducing the pollution’s emission. In the literature, the time spent at a waste collection point (WCP) is considered as the average time, or it is not included at all. Time spent at a WCP is determined by the processes of picking up, emptying, and putting down the waste containers and the factors specific for different WCPs. Those factors impact the time spent at WCP significantly. Excluding time spent at a WCP or taking the average of that in the planning approach may lead to the inaccurate estimation of total collection time. The aim of this article is to present the multiple regression model for estimating time spent at a WCP. We analyzed the impact of the WCP factors (i.e., building type and number of containers) on the time that a garbage truck spends at it. We initially considered seven chosen factors, five categorical and two numerical. Based on this, we developed the multiple regression model based on linear regression use. Later, the proposed model was validated based on data obtained from the municipal company operating in Wroclaw city, Poland. The study confirmed that the defined factors significantly affect garbage truck’s time spent at a WCP and should be taken into account during waste collection planning processes’ performance.

Prediction of container filling for the selective waste collection in Algeciras (Spain)

The aim of this study is to create an intelligent system that improves the efficiency of garbage collection, (cardboard waste, in this particular case). The number of cardboard containers to be collected each day will be determined based on a prediction made on the filled volume recorded in each container. It will be reflected in the cost and fuel savings, reducing emissions and contributing to environmental sustainability. These results will allow planning the sequence of waste removal, which means the optimal collection route considering restrictive parameters such as the type of truck, the location of containers, collection times by zones, and the availability of working staff.A filling prediction system is proposed based on real historical data provided by the current waste collection company in Algeciras (ARCGISA). To achieve this objective, an intelligent system is designed using predictive analytics and several methods based on machine learning, modelling the collection system as a classification model, comparing the results from a statistical point of view (using sensitivity, specificity, etc.). The results obtained with the best-tested method indicate an improvement average rate of 26% in sensitivity performance index and 67% in specificity performance index.Currently, waste collection is carried out without predictive analysis. The relevance of an efficient waste collection system is becoming increasingly important. Achieving optimal waste collection will result in improved service to citizens, cost savings for the administration, and significant environmental improvements.

Disposal of Personal Protective Equipment during the COVID-19 Pandemic Is a Challenge for Waste Collection Companies and Society: A Case Study in Poland

One of the social measures applied during the COVID-19 pandemic has been the use of personal protective equipment (PPE)—face masks and gloves. As a result, this waste category has expanded enormously. This study investigates waste management issues from multiple perspectives, including local governments, waste collection companies, and individual citizens in Poland using a telephone survey for institutions and an online questionnaire for individuals. The results of this study show that approximately 80% of local governments in the Silesian region have applied special measures for handling and collection of waste PPE. Only 13% of waste collection companies have applied special collection schedules for the waste generated at quarantine collection points due to the high costs of changing collection schedules, providing additional vehicles, and paying for more labor. The information campaigns focusing on new methods of PPE waste collection have been difficult to introduce on a large scale, and citizens need better information regarding how to handle and dispose of waste PPE. Results indicated the most helpful method in supporting waste PPE collection would be automatic PPE dispensers with waste PPE collection options and waste bags of a designated color. The respondents identified waste PPE pollution of the environment as an issue and the necessity for proper recovery of this waste stream.

Combining an artificial intelligence algorithm and a novel vehicle for sustainable e-waste collection

Mobile collection of waste electrical and electronic equipment is a collection method that is convenient for residents and companies. New opportunities to use mobile apps and internet applications facilitate the ordering of waste pickups from households and preparation of a collection plan for a waste collection company. It improves the secondary raw materials collection in a circular economy approach after recycling waste equipment.This study presents a combined methodology for improving the efficiency of e-waste collection. An online e-waste collection supporting system uses a Harmony Search algorithm for route optimization of waste collection vehicles. The results of the optimization are better compared to other artificial intelligence algorithms presented in the literature and the number of visited collection points is higher from 1.2%–6.6% depending on the compared algorithm. To increase the efficiency of waste loading and packing, a novel collection vehicle body construction is presented. The design includes the convenient loading of waste from both sides of the vehicle and the rear side being equipped with a hydraulic lift. The proposed vehicle model can be used for e-waste collection in places with limited parking spaces or where the parking time is limited, such as in densely populated city centers. The waste equipment packing efficiency increases and eliminates the necessity of including a container loading problem in the algorithm and allows increasing waste equipment number loaded in a collection vehicle.

Application of deep learning object classifier to improve e-waste collection planning

This study investigates an image recognition system for the identification and classification of waste electrical and electronic equipment from photos. Its main purpose is to facilitate information exchange regarding the waste to be collected from individuals or from waste collection points, thereby exploiting the wide acceptance and use of smartphones. To improve waste collection planning, individuals would photograph the waste item and upload the image to the waste collection company server, where it would be recognized and classified automatically. The proposed system can be operated on a server or through a mobile app. A novel method of classification and identification using neural networks is proposed for image analysis: a deep learning convolutional neural network (CNN) was applied to classify the type of e-waste, and a faster region-based convolutional neural network (R-CNN) was used to detect the category and size of the waste equipment in the images. The recognition and classification accuracy of the selected e-waste categories ranged from 90 to 97%. After the size and category of the waste is automatically recognized and classified from the uploaded images, e-waste collection companies can prepare a collection plan by assigning a sufficient number of vehicles and payload capacity for a specific e-waste project.

Reduction of work accidents through the implementation of containers for solid waste collection

The activity of waste collection is fundamental for preserving human health and the environment. As the world population increases, so does the waste production, consequently leading to a higher number of professionals involved in the collection activity. The objective of this study was to identify the main causes of accidents in urban waste collection and to verify if the implementation of containers would reduce the number of accidents in the sector. The causes were identified by analyzing accidents in two waste-collection companies for 4 years. Company A had 3,859 employees with 756 registered accident cases, while company B had 2020 workers with 189 cases. In total, it was analyzed 945 accident cases from urban waste collection. One municipality from company A which implemented the highest number of containers was studied thoroughly to verify if the implementation of containers reduces the number of accidents. The analysis shows that the household collection had the highest accident rate, with 65.61%. Sharp materials and falls were the leading causes of accidents, representing 53% in the company A and 62% in the company B. After containers implementation, the number of accidents caused by sharp materials and falls decreased from 37 without the container in 2014, to 18 with the container in 2015, and 11 with the container in 2016. It was concluded that the implementation of containers improves occupational safety and health during the urban cleaning process. Further studies should be conducted in order to improve the working conditions in the urban cleaning sector.

Medical waste collection considering transportation and storage risk

We consider a Periodic Load-dependent Capacitated Vehicle Routing Problem (PLCVRP) encountered by healthcare centers and medical waste collection companies for the design of a weekly inventory routing schedule to transport medical wastes to treatment sites. In addition to minimization of transportation risk, occupational risk related to temporary storage of hazardous wastes at the healthcare centers is considered. The transport risk on each arc is dependent on the weight of hazardous medical waste on the vehicle when it traverses that arc. We devise a decomposition based heuristic algorithm to solve this problem. We analyze the characteristics of the PLCVRP’s solutions with respect to four different criteria: (i) transport and occupational risk, (ii) transport risk, (iii) occupational risk, and (iv) transportation cost. Solving different versions of PLCVRP reveals that minimizing both transport and occupational risk on the network can aid decision makers to develop a better routing schedule in terms of the imposed risk of hazardous medical waste. Experimental results confirm the efficiency of our heuristic. We present a case study to illustrate solution attributes obtained by our solution methodology. The case study is based on medical waste management in Dolj, Romania.

Solid Waste Management Challenges and Its Impacts on People’s Livelihood, Case of Kinyinya in Kigali City

The main intention of this study was to assess the solid waste management challenges and their impacts on people’s livelihood. Specifically, the study evaluated the methods and techniques used for waste collection, transportation and deposit to the landfill by households, and companies in Kinyinya sector. A survey was conducted to collect data from household, waste collection company and field. Household waste collection, transportation and deposit illustrated different challenges which impede the sustainable treatment and disposal of waste. Findings pointed out poor deposit of wastes, failure to pay waste collection fees, poor assessment before selecting waste landfill and poor working condition of companies in charge of waste collection, transportation as the major challenges toward waste management in Kinyinya. The findings illustrated that only 33.25% of households separated decay from undecayed waste and 66.75% couldn’t perform such activities. The findings indicated that members of some households suffered waste borne diseases from poor waste management. The linear correlation coefficient has shown 84.5% of correlation level between waste management challenges and people’s livelihood (r = 0.845) and this correlation is statistically significant. Thus, poor waste management is one among factors of poor people’s livelihood. The adaptation of segregation of waste at the household, strengthening company capacity and training workers at the landfill would save life and reduce exposure of both household and landfill workers.

Overcoming managers’ myopic decisions in a waste collection company

Purpose The purpose of this paper is to show how the changing interrelationships between fleet management, human resources and outsourcer capacity areas are likely to counterbalance managerial policies, thereby generating a performance decay. The use of system dynamics modelling in a waste collection company offered an effective contribution to support decision makers to overcoming myopic decisions. Design/methodology/approach Literature review and a case study analysis (including interviews with company actors and data gathering) offered the basis to build a system dynamics model. The model built was then used to run simulations sessions to assess alternative investments decisions. Findings Simulation results show that understanding cause-and-effect relationships between company sub-systems can help managers to shift the focus of their decision process from a single department to the whole business system. Further, the paper offers three alternative scenarios (myopic, reactive and proactive) from which to learn how to design effective long-term sustainable policies. Research limitations/implications The simulation model was developed based on a literature review and a single-case study. Although it offers a useful contribution in the investigated case, to generalise its results, additional application to waste collection companies would be desirable. Practical implications The findings of the study have implications for public decision makers and those scholars investigating how to discourage the adoption of myopic decisions in complex environments. Originality/value To the best of our knowledge, only few studies investigated how the fleet management is likely to impact on the performance of waste collection companies. This study offers a contribution in this direction.