A dynamic approach for the multi-compartment vehicle routing problem in waste management

In recent years, the integration of sustainable principles into the Vehicle Routing Problem (VRP) for efficient waste management has gained significant attention. This paper provides an overview of advancements in multi-objective mathematical programming (MP) models and the optimization techniques for sustainable waste management practices within the VRP framework. Sustainable waste management practices in the context of the VRP involve optimizing routes and schedules aim to reduce the environmental impact of waste collection. It investigates the integration of multi-objectives with sustainability criteria, including social, economic, and environmental considerations. Furthermore, it surveys various optimization methodologies applied in waste management to enhance efficiency and sustainability practices. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was employed as a formal systematic review guideline for data gathering. Data was obtained from studies conducted between 2017 and 2023. The analysis included a total of 18 papers from online sources and databases. Based on the literature review, it has been observed that the majority of the research focused on employing Mixed-Integer Linear Programming (MILP) models to tackle the optimization problem for waste management. The literature survey demonstrated significant contributions in computational performance, cost-effectiveness, operational efficiency, and utilization of real-world data by improving the solution approaches, aiming to prioritize economic, social, and environmentally friendly solutions. The paper aims to serve as a convenient reference for researchers and practitioners seeking information on using the MP model and solution approaches to optimize VRP for waste management.

Dynamic vehicle routing problem (DVRP) with single depot has received increasing interest from engineers and scientists. Dynamic multi-depot vehicle routing problem (DMDVRP), an extension of DVRP, however, has not received much attention. In our paper, a distance-based clustering approach is introduced to simplify the DMDVRP by allocating each customer to its nearest depot. Thus, DMDVRP is decomposed to a sequence of DVRPs. An improved ant colony optimisation (IACO) with ant-weight strategy and mutation operation is presented to optimise vehicle routing problem (VRP) in this paper. Moreover, to satisfy the real-time feature of DMDVRP, the nearest addition approach is used to handle the new orders occurring during a time slice on the basis of VRP solution. Finally, the computational results for 17 benchmark problems are reported to validate that IACO with the distance-based clustering approach is more suitable for solving DMDVRP.

The Vehicle Routing Problem (VRP) is a complex and high-level set of routing problems. Two of its important variants are the Dynamic Vehicle Routing Problem (DVRP) and the Green Vehicle Routing Problem (GVRP). The first one has become a challenging research topic in the last two decades, in which not all informations are known in advance, but are revealed as the system progresses. The second one is seen as a new application and solution in new logistics patterns, more specifically, for finding routes of vehicles to serve a set of customers while minimizing the total amount of CO 2 emissions, by increasing the loading rate and reducing the number of empty trips could reduce from 10% to 40% km traveled and therefore CO 2 emissions [1]. In this paper, we combine these two variants (DVRP and GVRP), where we try to minimize, in the dynamic environment, the greenhouse gas especially the carbon dioxide CO 2 , which is the immediate consequence of the depletion of the ozone layer and time duration. We will call this combination the Dynamic Green Vehicle Routing Problem (DGVRP). To study this new problem, we present the technique employed to estimate the amount of CO 2 emissions, the emission matrix and integrate them into the DGVRP model, then we propose the hybridization based on Ant Colony Optimization (ACO) algorithm with a Large Neighborhood Search (LNS) algorithm to solve our problem. The effectiveness of this approach is tested on a set of the dynamic green problems instances, which are adopted in this work from the static GVRP benchmark datasets.

Purpose This study aims to explore how digital platforms (DPs) contribute to value co-creation in municipal solid waste (MSW) management systems. Design/methodology/approach The present paper conducts an explorative analysis using single case study methodology. The case in question involves a DPs operating in Italy. Findings Empirical analysis shows that DPs help engage citizens in MSW and reduce the fragmentation in waste management systems by fulfilling a brokerage role that connects citizens, municipalities and waste management companies. The development of bidirectional knowledge and resource flow among actors contributes to better waste recycling processes, as well as fosters economic, environmental and social value co-creation in a complex public service. Research limitations/implications This research is limited to a single case study within the Italian context, which may influence the generalizability of the findings. Future research could expand the scope to include multiple case studies across different geographical regions. Practical implications For practitioners and policymakers, this paper underscores the strategic benefits of adopting DPs in MSW management systems and thereby improving public service delivery. Social implications The case analysis highlights that DPs can assist public actors in achieving numerous sustainable development goals by enhancing recycling rates and activating learning mechanisms among citizens. Originality/value This study contributes to literature by connecting different fields of research (i.e. waste management and public management) and using network theory to show how DPs can contribute to the economic, environmental and social sustainability of MSW while generating relevant benefits for the actors involved.

A comparison of waste management in Guangzhou and Hong Kong

Practical experience of solid domestic waste (MSW) management in Ukraine and developed countries is analyzed. Theoretical volumes of MSW accumulation taking into account statistical factors are studied. The generalized method of MSW accumulation volumes allows forecasting their formation from the factors and evaluating the morphological composition of MSW in the region. The system for optimizing community waste management at the collection and disposal stage with the quality of the optimality criterion has been proposed. The degree of recycling and the costs of collecting and transporting waste should be taken as a criterion for optimising the urban waste management system at the collection and disposal stage. The quality analysis of the waste management system in the Zhytomyr region made it possible to identify the main problems in municipal waste management and the main reasons for their occurrence. The survey shows that the main problem in the area of waste management is the low efficiency of the existing management system, accompanied by the introduction of outdated and inefficient management methods with the lack of effective interaction of all participants in the waste management process and, above all, the lack of public involvement in solving the problem. The authors concluded that at the present time Zhytomyr city and Zhytomyr Region faced the following problems in the area of solid waste management: the number of spontaneous landfills has increased; the number of modern waste collection bins is insufficient and there are no bins for separate waste collection; the quality of solid waste collection services is inadequate; there is no recycling plant in Zhytomyr; large amount of household waste in the city landfill and absence of monitoring of its impact on the environment.

Environmental and economic feasibility of an integrated community composting plant and organic farm in Malaysia

Standard methods for assessing the environmental impact of waste management systems are needed to underpin the development and implementation of sustainable waste management practice. Life cycle assessment (LCA) is a tool for comprehensively ensuring such assessment and covers all impacts associated with waste management. LCA is often called “from cradle to grave” analysis. This paper integrates information on the greenhouse gas (GHG) implications of various management options for some of the most common materials in municipal solid waste (MSW). Different waste treatment options for MSW were studied in a system analysis. Different combinations of recycling (cardboard, plastics, glass, metals), biological treatment (composting), and incineration as well as land-filling were studied. The index of environmental burden in the global warming impact category was calculated. The calculations are based on LCA methodology. All emissions taking place in the whole life cycle system were taken into account. The analysis included “own emissions,” or emissions from the system at all stages of the life cycle, and “linked emissions,” or emissions from other sources linked with the system in an indirect way. Avoided emissions caused by recycling and energy recovery were included in the analysis. Displaced emissions of GHGs originate from the substitution of energy or materials derived from waste for alternative sources. The complex analysis of the environmental impact of municipal waste management systems before and after application of changes in MSW systems according to European Union regulations is presented in this paper. The evaluation is made for MSW systems in Poland.

In this study, an inexact fuzzy-probabilistic programming (IFPP) method is advanced for developing optimal municipal solid waste (MSW) management strategy with uncertain information. The IFPP can support the assessment of risk of violating constraints associated with fuzzy and random features. The developed method is applied to a case study of long-term MSW management planning in the city of Changchun, China. Violations for transfer-station capacity constraints are allowed under a range of probability and possibility levels, which are related to trade-offs between the system cost and the constraint-violation risk. The results indicate that useful solutions for planning the MSW management practices have been generated. They are valuable for supporting the identification of efficient waste-flow allocation patterns, the long-term capacity planning of the city’s waste management system, and the formulation of local policies regarding waste management under uncertainty.

Developments in Municipal Solid Waste Management (MSWM) systems depend on socio-cultural, political, economic, and environmental issues. The ability to assess and evaluate the level and nature of these relationships plays a critical role in measuring the performance level vis-à-vis sustainability of waste management systems. The current criteria adopted for assessing waste management performance do not capture an accurate and comprehensive representation of MSWM scenarios from collection to disposal. Hence the methodologies do not accurately measure the level of impacts resulting from waste management systems or, indirectly, the environmental, economic, social, and cultural costs of MSWM. This research develops a waste management performance assessment protocol that captures all relevant components of waste management processes. The methodology is based on emission as the indicator of choice for assessing the performance of a city-wide or regional waste management system. The study developed a framework, Comprehensive Emission Quantification Model (CEQ-Model), for measuring the sustainability of the MSWM system hinged on process-based emission modelling. This framework incorporated aspects of the Intergovernmental Panel on Climate Change (IPCC) Guidelines and Life Cycle Thinking (LCT), framed using carefully selected MSWM scenarios in New Zealand. In a ranked cumulative emission quantification assessment of four Territorial Authorities (TA), the research determined the performance level of each TA relative to others. Auckland Council, with a total emission of 4.272x1012 KgCO2-e generated from disposing of 2,425,022 tonnes of waste, was the most unsustainable territory, followed by Rotorua District with total emission of 6.666x10 10 KgCO2-e from 45,000 tonnes of waste, and Waikato District with emission of 5.380x10 10 KgCO2-e from 29,796 tonnes. In comparison, the most sustainable TA is Opotiki District with total emission of 2.314x10 9 KgCO2-e from 1,450 tonnes of waste, giving emission per tonne of waste per year as 1.762 GgCO2-e, 1.806 GgCO2-e, 1.6 GgCO2-e, and 1.481 GgCO2-e for Auckland Council, Waikato District, Opotiki District, and Rotorua District respectively.

Modular life cycle assessment of municipal solid waste management

The vehicle routing problem (VRP), as a classic combinatorial optimization problem, has always been a hot research topic in operations research. In order to gain a deeper understanding of the VRP problem, this work uses the knowledge graph to comprehensively analyze and summarize the literature related to VRP from 1959 to 2022 in the Web of Science (WoS) database. Firstly, according to the basic statistical information of the literature, the annual publications, the authors, their institutions and countries, the keyword co-occurrence, and the literature co-citation network are analyzed to comprehensively summarize and generalize the research on VRP and predict its future development trend. The results show that, in the past 60 years, there have been abundant changes in the research on VRP. The United States and China have made the most important contributions in the field of VRP. According to the WoS literature retrieval results and classification methods, the VRP models and their solutions are comprehensively classified, and the model solving algorithms are divided into exact algorithms, heuristic algorithms, metaheuristic algorithms, hyper-heuristic algorithms, machine learning, etc. The results show that the development of information computing technology plays an important role in research on the VRP problem, and dynamic VRP, hyper-heuristic algorithms, deep reinforcement learning, etc. are the future development directions of the VRP model and its optimization. The results of this research can provide help and guidance for beginners and scholars outside the industry to comprehensively understand the development and research hotspots of VRP.

A vehicle routing problem involves finding a set of optimal route for a fleet of capacitated vehicles which are available at a location to service the demands of a set of customers. In its simplest form, a customer is required to be visited once and the capacity of a vehicle must not be exceeded. In this paper, a review of four common and applicable variants of the vehicle routing problem, namely, capacitated vehicle routing problem, vehicle routing problem with time windows, periodic vehicle routing problem and the dynamic vehicle routing problem, are considered based on formulation techniques, methods of solution and areas of application. A summary table is presented for each variant to emphasis some key features that represent direction of current research.

Ethiopia is striving to enhance waste management and energy access but lacks a clear understanding of utilizing waste for energy generation. This underscores the necessity of developing power generation technologies that utilize locally sourced materials. While numerous studies have highlighted the production of municipal solid waste in various Ethiopian cities, there is a lack of localized case studies focusing on specific regions and the composition of waste about small-scale power generation systems that use municipal solid waste as fuel. This study seeks to characterize selected municipal solid waste as a fuel source, as well as to design and develop a small-scale power generation system using locally available materials to utilize municipal solid waste as a fuel source. The Engineering Equation software tool was utilized for system modelling and design. The EA1112 Flash CHNS/O analyzer measured the ultimate analysis of waste samples, while a K-type thermocouple was used to measure combustion temperature. The modelling indicated that the prototype could process 32.5 kg/hr of dry municipal solid waste, with an overall efficiency of 35.2%, generating a theoretical power of 300W. However, in the experiment, the system produced 18.7 W by combusting 125 kg/hr of municipal solid waste, resulting in the production of 68.4 kg/hr of steam. The study highlights the need for further efficiency improvements in the combustion system and the thermal-to-mechanical energy converter unit, such as the turbine system. The study shows a feasible way to create a small power generation system using local materials and expertise, which can address energy shortages and waste management problems. This study particularly attempted to fill the spatial research gap of municipal solid waste-based small-scale power generation plants in Ethiopia. Local businesses and industries should consider adopting this technology to overcome these challenges.

The waste management system in the city of Čačak was analyzed, from the primary selection of waste at the place of its origin, until its disposal at the regional sanitary landfill "Duboko" in Užice. A review of the planning documents brought for the area of the city of Čačak revealed problems in waste management (waste collection, primary separation, transport). Inadequate waste management and its disposal without any treatment is a growing environmental problem of local governments. Although waste management in Serbia is regionalized, this does not mean that local self-government units have lost their competence in this area. The purpose of the paper is to recognize and present its greatest weaknesses through the analysis of the integrated waste management system, as well as to offer possible solutions to the given problems.