Waste Collection Problem Research Articles

A waste collection problem with service type option

Efficient solid waste management is one of the most relevant issues for urban communities. With regard to the service type of household waste collection, there are two approaches in practice: when collecting household waste via a door-to-door system, the collection vehicles drive down all the streets to empty the garbage cans on the curb. Using a bring system, waste is accumulated at central collection sites with a larger capacity. While residents do have to travel an additional distance to dispose of their waste at these central collection sites, a bring system can reduce the distance to be covered by collection vehicles because they no longer have to drive down all the streets. To combine the advantages of both systems, in this article the service type decision is introduced. The corresponding waste collection problem with service type option (WCPSTO) is modeled as a new variant of a periodic location routing problem and an adaptive large neighborhood search-based solution approach is proposed. This solution approach not only solves the newly presented problem, but also outperforms a solution algorithm for a related waste collection problem seen in the literature, which can be seen as a special case of the WCPSTO.

IoT Analytics and Agile Optimization for Solving Dynamic Team Orienteering Problems with Mandatory Visits

Transport activities and citizen mobility have a deep impact on enlarged smart cities. By analyzing Big Data streams generated through Internet of Things (IoT) devices, this paper aims to show the efficiency of using IoT analytics, as an agile optimization input for solving real-time problems in smart cities. IoT analytics has become the main core of large-scale Internet applications, however, its utilization in optimization approaches for real-time configuration and dynamic conditions of a smart city has been less discussed. The challenging research topic is how to reach real-time IoT analytics for use in optimization approaches. In this paper, we consider integrating IoT analytics into agile optimization problems. A realistic waste collection problem is modeled as a dynamic team orienteering problem with mandatory visits. Open data repositories from smart cities are used for extracting the IoT analytics to achieve maximum advantage under the city environment condition. Our developed methodology allows us to process real-time information gathered from IoT systems in order to optimize the vehicle routing decision under dynamic changes of the traffic environments. A series of computational experiments is provided in order to illustrate our approach and discuss its effectiveness. In these experiments, a traditional static approach is compared against a dynamic one. In the former, the solution is calculated only once at the beginning, while in the latter, the solution is re-calculated periodically as new data are obtained. The results of the experiments clearly show that our proposed dynamic approach outperforms the static one in terms of rewards.

Multi-Day Waste Collection and Transportation Problems with Selective Collection and Split Delivery

Multi-Day Waste Collection and Transportation Problems with Selective Collection and Split Delivery

VRP variants applicable to collecting donations and similar problems: A taxonomic review

This paper presents a taxonomic review of Vehicle Routing Problem (VRP) with Time Windows (VRPTW), Pick-up and Delivery Problem (PDP), and Periodic Vehicle Routing Problem (PVRP). We focus on the problems of collection goods and similar. The applications of these models are typical like found in the literature; however, not applications specifically about collecting donations were found. Because of concern for the environment, social equity, and business efficiency, specific research fields related to green and reverse logistics have arisen; thus, optimization of waste (second-hand goods, food, recyclable/no recyclable waste, etc.) collection routes gain interest. In the literature reviewed, we found several VRP models of goods collection applied to picks-up of returned items, End-of-Life (EOL) products, Municipal Solid Waste collection (MSW), and Waste Collection Problem (WCP). The primary purpose of this paper is to structure the taxonomy of VRPTW, PDP and PVRP problems applicable to collecting donations according to its features, solution methods, and mathematical formulation. Likewise, provide the reader with an outline orderly and differentiated from the VRP models associated with pick up items and delivery orders (VRPPD), backhauling customers (VRPB), collection waste, and similar problems to propose our problem. For clarity, Appendix A includes the acronym used in these types of problems. This paper is part of a larger research project called “CVRPTW model applied to collecting food donations,” intending to contribute to a new perspective on the routing problems little explored.

A bi-level multi-objective location-routing model for municipal waste management with obnoxious effects.

Municipal waste management is a complex problem. This paper develops a bi-level multi-objective location-routing model for municipal waste management that considers the interests of both the government and the sanitation companies. The government as the leader decides on the location and scale of the waste recycling centers to reduce the obnoxious effects and ensure cost effectiveness, and the sanitation company as the follower decides on the waste collection routing plans based on the government-approved locations to minimize the logistics cost. An improved hybrid NSGA-II is then developed to solve the proposed model. Two initial solution methods are employed: clustering for the leader and a Clarke and Wright method for the follower. Non-dominated sorting and best-cost route crossover operator are used to improve the effectiveness of NSGA-II. Based on Prins (24 instances) and Barreto (13 instances) benchmarks, the experimental results indicated that the improved operator had strong competitiveness and a better performance than previous methods, with the improved algorithm achieving the best average gaps of 0.18% and 0.24% and improving the best-known solutions in some instances. The model and solution methodology are illustrated using a waste collection problem in Tianjin, from which practical insights are derived.

Formation of Ecological Culture Among Students of General Education Organizations in the Field of Solid Municipal Waste Management

The problem of handling solid municipal waste, which is formed during the life of a modern person, is becoming more and more urgent every day. The growth of consumption in modern society entails an increase in the formation of waste, which must no longer be stored, but subjected to recycling or recycling for further use. The solution of this problem, in addition to the technical and organizational component, is possible by forming a culture of solid municipal waste management (hereinafter MSW) among the population, that is, the formation of an ecological culture. The article describes the implementation of the social project “Organization of environmental education and formation of environmental culture of the younger generation in the field of solid municipal waste management” of the Transbaikal State University. During the implementation of the project, the level of environmental culture of schoolchildren was studied by testing in accordance with age. The developed educational and educational program, which includes a set of measures for training and environmental education of general education organization students, helped to motivate them to properly handle waste and form a responsible attitude to nature. Diagnostics formation level of the ecological culture of the younger generation allowed us to state the presence of a problem, namely, the insufficient (low and average) formation level of the ecological culture of general education organization students. Environmental classes and actions allowed students to form an idea of the problems of waste disposal, as well as their understanding of the need for separate collection and recycling of waste. Environmental education of the younger generation has changed their attitude to the problem of separate waste collection and contributed to the formation of environmental consciousness. Keywords: environmental education, environmental culture, younger generation, municipal solid waste, waste management

A hybrid metaheuristic for smart waste collection problems with workload concerns

In this paper, a hybrid metaheuristic is developed to solve the smart waste collection problem with workload concerns. It is composed by: (i) a look-ahead heuristic aiming at deciding the days in which collection is necessary and which bins need to be collected (must-go) considering the present bin fill levels and future bin fill level predictions; and (ii) a simulated annealing/neighborhood search algorithm to choose the bins that are profitable to collect and the best route(s) to visit the bins. This algorithm was developed to find solutions within a relatively short amount of time (we considered two hours as reference), as required for practical operations. The proposed hybrid metaheuristic is applied to randomly-generated test instances of sizes up to 500 bins and to a real case study of recyclables collection, leading to results that demonstrate its effectiveness and usefulness in practice when dealing with large-size instances. For the real case study, involving a major waste management company in Portugal, the profit achieved by the hybrid metaheuristic is at least 45% higher than the profit obtained by the company, and, at the same time, compliance with maximum shift duration and route workload balance is clearly better when the metaheuristic is used than in current operations.

Hybrid wind-municipal solid waste biomass power plant location selection considering waste collection problem: a case study

ABSTRACT Significant increments of energy demand and the need to decarbonize the existing energy systems motivate policymakers to utilize renewable energy resources. Accordingly, this paper suggests a hybrid electricity generation system that operates with wind and municipal solid waste biomass to generate monotonous currents and protect the environment by using a portion of the urban wastes. To select a hybrid power plant location, Z-number data envelopment analysis is employed considering economic, social, environmental, and strategic factors, in addition to reliability of fuzzy data. Furthermore, a routing problem is solved by the particle swarm optimization algorithm to calculate the optimal cost of urban waste gathering. As a case study, the model is applied to thirty-one cities in Iran; Shahrbabak, Meymeh, and Birjand are three cities selected as optimal hybrid power plant locations. Finally, the sensitivity analysis results indicate the importance of globally adopting land cost and distance from power distribution network factors.

Separate collection of solid household waste by residents of multi-family homes

Introduction. The problem of solid household waste management, analyzed in the context of sustainable development, is relevant both in Russia and worldwide. On the one hand, it deals with vast legitimate and illegitimate landfills, polluting the environment. On the other hand, it deals with the depletion of natural resources and the potential usability of latent reserves of recyclable waste. It is inefficient to accumulate mixed waste and build recycling capacities, since they are accompanied by atmospheric pollutions. Separate collection of waste has a great potential. According to the estimates, Russia’s waste management system will move to a new level when local waste management companies come into operation. This new level will ensure environmental protection and higher standards of living. However, the intersectoral problem of separate waste collection cannot be solved by local waste management operators. This problem deals with urban development patterns and urban economies of the RF subjects, as well as the Russian industries, that use recyclable materials.
 Materials and methods. The co-authors have applied the system analysis of the research literature, statistical data and regulatory documents, as well as process modeling.
 Results. The co-authors have analyzed the engineering model of separate waste collection, implemented by residents of multi-family homes within the framework of the “nature – economic activities – nature” pattern. The accumulation of hazardous and oversized waste is organized as the separate subsystems of the waste management system implemented by the residents of a multi-family home.
 Conclusions. The co-authors propose to modify the system of household waste management to prevent the over-accumulation of substantial amounts of mixed household waste in waste containers near residential houses and in waste collection rooms. The introduction of ecologically friendly innovations is needed at each stage of the life cycle of any product.

An Integrated Territory Planning and Vehicle Routing Approach for a Multi-Objective Residential Waste Collection Problem

In this paper, we address a multi-objective residential waste collection problem with an integrated territory planning and vehicle routing approach. Dividing the problem into territories enables drivers to carry out the same route every week so they get familiar with it and residents put out their bins at the appropriate time. Another benefit is to reduce the computation time for large problems, since the complex characteristics of the involved vehicle routing problem make it otherwise difficult to solve. There are three characteristics that are important for good territory planning: minimum overlap, minimum travel time, and balanced workload. The purpose of this paper is to investigate the influence these three objectives have on each other, since they might be contradictory. Moreover, an Adaptive Large Neighborhood Search (ALNS) algorithm is developed for this specific problem which uses a K-means algorithm to generate the initial solution for territories. The results with the three objectives are shown to be useful for planners seeking to make informed decisions through the trade-off across different solutions with the Pareto frontiers provided. Moreover, the ALNS algorithm is shown to find good quality solutions in a reasonable computational time.

An exact routing optimization model for bio-waste collection in the Brussels Capital Region

This paper presents a routing optimization model for a wide range of waste collection problems which allows for multiple depots with homogeneous, capacitated vehicles, intermediate stops at multiple processing facilities, and multiple pick-ups per waste collection location. By minimizing collection routing and vehicle investment costs, the model estimates the total transportation costs for a given network design and waste volumes to be collected at different demand points. The number of feasible routes is severely reduced by restricting the number of subsequent pick-up location visits. The model’s use is illustrated through assessing four future, realistic bio-waste collection scenarios of the Brussels Capital Region (BCR). The scenarios differ with respect to assumptions on future collection rates, joint versus separate collection of food and green waste, and number and locations of processing facilities. The results show that the highest cost reduction can be achieved through joint collection of food and green waste combined with three composting locations. Moreover, we found that introducing multiple processing facilities significantly increases the complexity of the waste collection problem.

GRASP with ALNS for solving the location routing problem of infectious waste collection in the Northeast of Thailand

This research proposes a heuristic to solve the problem of the location selection of incinerators and the vehicle routing of infectious waste collection for hospitals in the Northeast of Thailand. The developed heuristic is called the Greedy Randomized Adaptive Large Neighborhood Search Procedure (GRALNSP)and applies the principles of the Greedy Randomized Adaptive Search Procedure (GRASP) and Adaptive Large Neighborhood Search (ALNS) in the local search. The results from GRALNSP are compared with those from the exact method processed by the A Mathematical Programming Language (AMPL) program. For small-sized problems, experiments showed that both methods provided no different results with the global optimal solution, but GRALNSP required less computational time. When the problems were larger-scale and more complicated, AMPL could not find the optimal solution within the limited period of computational time while GRALNSP provided better results with much less computational time. In solving the case study with GRALNSP, the result shows that the suitable locations for opening infectious waste incinerators are the locations of Pathum Ratwongsa district, Amnat Charoen province and Nam Phong district, Khonkaen province. An incinerator with a burning capacity of 600 kilogram/hour is used at both locations. The monthly total distances for infectious waste collection are 24,055.24 and 38,401.88 kilometers, respectively, and the lowest total cost is 6,268,970.40 baht per month.

ЭКОЛОГИЧЕСКИЙ ИМИДЖ ПРИБРЕЖНЫХ ДЕСТИНАЦИЙ РЕСПУБЛИКИ КРЫМ

The paper analyzes various approaches to defining the definitions of «image» and «environmental image». The differences between the concept of «image» and «reputation» are revealed. The importance of coastal destinations in the development of tourism in the territory of the Republic of Crimea has been determined. The factors influencing the ecological image of coastal destinations are highlighted. They are grouped into six main groups: political; economic; informational; technical and technological; resource and consumer. It has been established that the forms and scales of recreational resource use and resource consumption on the territory of the peninsula do not correspond to the volume and structure of its natural resource potential; insufficient economic and environmental efficiency of recreational activities is often noted. The influence of the ecological aspect on the formation of the tourist image of the Republic of Crimea is analyzed. Еhe main reasons contributing to the formation of a negative ecological image of Crimea are the consequences felt by a tourist and associated with air pollution by emissions of harmful substances from stationary and mobile sources of pollution; unresolved problem of waste collection and disposal; pollution of the Black and Azov Seas with household and industrial wastewater; an increase in the recreational load on the natural complexes of coastal destinations; reduction of beach areas. Also, the formation of the image of the Republic of Crimea is associated with a number of problems caused by the desire of official sources to «embellish» reality and the desire of «well-wishers» to create an image of Crimea as an unjustifiably expensive, dirty and hazardous destination for health. State programs aimed at overcoming the ecological problems of the peninsula are analyzed.

Behaviour study of genetic operators for the solid waste collection problem: the municipality of Sidi Bou Said case study

Behaviour study of genetic operators for the solid waste collection problem: the municipality of Sidi Bou Said case study

Behaviour study of genetic operators for the solid waste collection problem: the municipality of Sidi Bou Said case study

Behaviour study of genetic operators for the solid waste collection problem: the municipality of Sidi Bou Said case study

Environmental education of students as a factor in social capital development (through the example of the practice of household waste separate collection)

Introduction. Social capital is a set of resources for human social interaction – social ties, rules of social exchange and trust. As the most important part of human capital, social capital becomes an indicator of society cohesion mainly in the matters of implementation of socio-system values – the survival and integrity of society, care for current and future generations. In this regard, the implementation of environmental values is an important direction in the development of social capital and a key task of students’ environmental education. Students’ environmental education is possible by solving an urgent social problem – the separate collection of household waste. This problem is becoming more and more relevant and discussed both at the regulatory and public levels. There is no formed public opinion – the understanding of possibilities and threats of this problem, the readiness of the population to participate in its solution. The purpose of the article was to analyze the views of students regarding the prospects and possibilities of solving the problem of separate waste collection in society, their readiness to independently participate in this practice, as well as to assess the possibilities of using this practice for the purpose of environmental education and increasing social solidarity. Materials and methods: 1) a qualitative substantive analysis of 200 students’ essays on the topic “Environmental Problems of My Region”; 2) a survey of 400 students of the Vyatka State University. Results. Students’ high willingness to practice separate waste collection against the background of other environmental practices (up to 70%, mostly girls (χ2=24.1, p=0.001), senior students (χ2=70, p=0.0). High cognitive interest in this problem is shown – 53% of students would like to study it further. Students consider the purchase of goods in biodegradable packaging as a first step towards reducing the amount of garbage (97% of students are ready to do this to varying degrees). First of all, students are ready to collect non-perishable waste – paper, plastic, glass, to a lesser extent – organic waste, metal, clothes, and shoes. More than half of the students understand that the practice of separate waste collection is a promising direction in the development of a civilized society, contributing to the improvement of yard aesthetics, improving the quality of the environment, preserving valuable resources, forests and, in general, manifestations of care for future generations. The main directions of work on environmental education and social solidarity are outlined on the basis of the data obtained.

Improving construction and demolition waste collection service in an urban area using a simheuristic approach: A case study in Sydney, Australia

Urbanization and population growth have resulted in a significant increase in the amount of generated construction and demolition (C&D) waste worldwide. Improper C&D waste management has led to a tremendous landfilled C&D waste, which has placed a great concern over its adverse impacts on the environment and natural resources. Appropriate C&D waste recycling mechanism as a remedial action saves our resources from deterioration, which can be guaranteed through a systematic apportion of the construction projects to C&D waste recycling facilities. Previous studies in waste collection routing problem have almost exclusively assumed that parameters are deterministic; however, uncertainty associated with waste collection routing makes deterministic models inapplicable to real-life systems. To tackle this problem, this research proposes a novel simheuristic based on an integrated simulation-optimization approach, in which an efficient hybrid Genetic Algorithm (GA) is applied in order to optimize vehicle route planning for C&D waste collection from construction projects to recycling facilities. A comparative analysis with existing well-known approaches is performed to represent the strength and effectiveness of the proposed approach. The results demonstrate high performance of the proposed simheuristic algorithm. This study has also benefited from a real case of construction projects apportion to recycling facilities in Sydney, Australia for better evaluation. This research strongly contributes to academics by lighting up the ways to optimize future waste collection problems in a wider range and more precise manner. Meanwhile, this study recommends to C&D waste decision makers and practitioners to allocate generated C&D waste to recycling facilities precisely with respect to the capacity of produced C&D waste, capacity of recycling facilities, distances, and vehicle capacities.

Sustainable smart waste classification and collection system: A bi-objective modeling and optimization approach

In the context of the “smart city”, information and communication technologies (ICT) have become indispensable in the planning and design of modern municipal solid waste management. Due to more waste varieties, there are urgent calls to implement waste classification worldwide, which promotes resource recycling to achieve sustainable development. In this paper, we present an ICT-based smart waste classification and collection system (SWCCS) that is abstracted as a bi-objective mathematical programming model to optimize the waste collection problem. To implement the proposed SWCCS effectively, we design a novel multi-objective hybrid algorithm based on the whale optimization and genetic algorithms (MOGWOA) with an improved convergence factor and a fast, non-dominated sorting method. A comparison of our algorithm with two classical multi-objective algorithms on generated test instances and on a real-world case shows that the proposed MOGWOA is more effective for optimizing the established model. This paper demonstrates how the ICT-based SWCCS works and how it can help sanitation companies improve waste collection both economically and environmentally.

Using modified metaheuristic algorithms to solve a hazardous waste collection problem considering workload balancing and service time windows

Hazardous wastes’ volume produced by human activities has increased in recent years. Consequently, associated risks involved in the treatment, recycling, disposing, and transportation of these hazardous materials have become more attractive for the researchers. In this study, we propose a new model for hazardous waste location routing problem. Appending the service time window and workload balance to the previous mathematical models can be taken into account as the major contributions of this study. Three objective functions including two systematic goals (cost and risk) and one social goal (workload balancing) have been considered for the model. Compatibility between wastes and a heterogeneous fleet of vehicles, which are rarely investigated in the literature, is discussed in this paper. Since the proposed model is classified as a multi-objective model, three multi-objective evolutionary algorithms, namely Non-dominated Sorting Genetic Algorithm II (NSGA-II), Pareto Envelope-based Selection Algorithm II (PESA-II), and Strength Pareto Evolutionary Algorithm II (SPEA-II) are employed. As two other innovations, an adaptive penalty function is developed and the PESA-II is modified by removing replicated solutions from its archive and their obtained results are discussed. Finally, by experimenting a number of test problems in different sizes, it is demonstrated that proposed modified PESA-II and SPEA-II perform better than NSGA-II in most of comparison metrics including feasible answers exploration, CPU time, spacing metric, inverted generational distance, quality metric, etc., whereas, NSGA-II creates more spread Pareto frontiers which are suitable for decision-maker to choose, from among a range of different options.

A bi-objective robust optimization model for hazardous hospital waste collection and disposal network design problem

The hazardous hospital waste (HHW) is one of the main problems in urban waste management, which requires the design and implementation of a special collection and disposal system. Hospital wastes were known as important hazardous waste to be efficiently disposed within a short operational time in order to prevent the spread of infections and diseases. In this research, a multi-objective robust optimization model was developed to design a collection and disposal network of HHW under uncertain condition. The objectives are to concurrently minimize the total cost including transportation and operations costs, and the total risk of transportation and operations. To solve the proposed bi-objective model, the augmented e-constraint method was employed. Moreover, the model validation is achieved using and solving several test problems in different sizes, and the analysis of the robust model was performed compared to the deterministic model. Finally, a real case study was conducted to demonstrate the applicability of the research’s methodology, which was done by determining Pareto front and performing a sensitivity analysis to evolve the managerial insights.