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Waste production and related environmental problems have caused urban services management many problems in collecting, transporting and disposal of waste. The purpose of this study is to design a new model for municipal waste collection vehicle routing problems with time windows and energy generating from waste. To this purpose, a bi-objective model is presented with the objectives of increasing the income of waste recycles and energy generation from waste and reducing emissions from environmental pollutants.

A bi-objective model is presented with the objectives of increasing income of recycles trade and energy generation and reducing emissions from environmental pollutants. Concerning the complexity of the model and its inability to solve large-scale problems, non-dominated sorting genetic algorithms and multi-objective particle swarm optimization algorithms are applied.

In this research, an integrated approach to urban waste collection modeling that coordinates the various activities of waste management in the city of Kermanshah and energy generation from waste are provided. Besides, this study calculates the criteria that show the environmental effects of municipal waste. The proposed model helps to collect municipal wastes in the shortest possible time in addition to reducing the total cost, revenues from the sale of recycled materials and energy production.

The proposed model boosts the current understanding of the waste management and energy generation of waste. The paper adds additional value by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.

Production of waste has been increased exponentially due to world industrialization and urban and machine life expansion. On the other hand, the outbreak of the COVID-19 coronavirus quickly became a global crisis. This crisis has added a large amount of waste to urban waste. The purpose of this study is to create cooperation between municipal waste collector contractors.

Thus, a mathematical model is proposed under uncertain conditions, which includes the volume of municipal waste and infectious waste including personal protective equipment and used equipment for patients. To reduce total costs, the results are evaluated with four cooperative game theory methods such as Shapley value, t value, core center and least core. Ultimately, the saved cost by cooperation in each coalition is allocated fairly among the contractors. Finally, a comparison was made between the solution methods based on the value of the objective function and the solution time.

The results indicate that the proposed cooperative method increases cost savings and reduces the fine of residual waste. Therefore, it can be mentioned that this kind of cooperation would finally result in more incentives for contractors to form larger coalitions. Genetic algorithms were used to solve the large-scale model.

The proposed model boosts the current understanding of waste management in the COVID-19 pandemic. The paper adds additional value by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.

Waste production and related environmental problems have caused urban services management many problems in collecting, transporting and disposal of waste. Since collecting and transporting waste are important parts of waste management budget, it is necessary to apply an appropriate method to reduce costs of collection. The aim of this study is to design a new model for urban waste collection vehicle routing problem with time windows and energy generating from waste.

A multiobjective model is presented with the objectives of minimizing cost of waste collection, reducing emissions from environmental pollutants and increasing income of recycles trade and energy recovery. Concerning the complexity of the model and its inability to solve large-scale problems, hyperactive genetic algorithms and multiple objective particle swarm optimization are applied.

The proposed model not only affects costs and income but also reduces the emissions of environmental pollutants. To solve the formulated model, multitarget approaches are applied on the processing site of Kermanshah city as a case study. The solutions of these algorithms and the exact method of partial constraints are compared and the outcomes are verified by numerical analysis by solving various examples in small, medium and large scales. The proposed model helps to collect urban wastes in the shortest possible time in addition to reducing the total cost, revenues from the sale of recycled materials and energy generation.

Waste collection is related to VRP issue. Considering the environmental requirements in waste management, the concept of green supply chain is approached. This study provides a better understanding of urban waste management by examining various articles and combining economic and environmental dimensions. Waste management with a green approach and energy production from disposable waste involves many common stakeholders.

This study suggests that proper waste management can generate revenue from municipal waste. Moreover, it reduces cost of collecting and emission of environmental pollutants. These findings could motivate companies to waste management with a sustainable approach.

The proposed model boosts the current understanding of the waste management and energy generation of waste. The paper adds additional values by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.

This study aims to propose an electronic waste collection and classification system to enhance social, environmental and economic sustainability by integrating data-driven technologies in emerging economies.

GM (1, 1) model under grey prediction is used in this study in order to estimate the trend of the amount of collected electronic waste in emerging economies.

It is revealed that the amount of collected electronic waste is increasing day by day, and within the framework of sustainability in the process of collecting and classification of electronic waste, digital technologies were found to be lacking. It has been determined that this deficiency, together with the increasing amount of electronic waste, has caused environmental, social and economic damage to emerging economies.

The main originality of this study is integrating electronic waste collection and classification processes with data-driven technologies and sustainability, which is a relatively new subject.

The main aim of this study is to understand the role of smart technologies and show the rankings of various smart technologies in collection and classification of electronic waste (e-waste).

This study presents a framework integrating the concepts of collection and classification mechanisms and smart technologies. The criteria set includes three main, which are economic, social and environmental criteria, including a total of 15 subcriteria. Smart technologies identified in this study were robotics, multiagent systems, autonomous tools, smart vehicles, data-driven technologies, Internet of things (IOT), cloud computing and big data analytics. The weights of all criteria were found using fuzzy analytic network process (ANP), and the scores of smart technologies which were useful for collection and classification of e-waste were calculated using fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR).

The most important criterion was found as collection cost, followed by pollution prevention and control, storage/holding cost and greenhouse gas emissions in collection and classification of e-waste. Autonomous tools were found as the best smart technology for collection and classification of e-waste, followed by robotics and smart vehicles.

The originality of the study is to propose a framework, which integrates the collection and classification of e-waste and smart technologies.

This study examines whether or not the waste management practices of the poor households living in squatters and low‐cost flats in Kuala Lumpur are conducive to the environment. With the aim of accomplishing the above, the study empirically assesses knowledge, attitude and behaviour of the urban poor concerning their household solid waste management. With primary data collected from the level of living condition and waste management practices of the urban poor, the study employed a multiplicity of statistical techniques such as t‐tests of equality of means, one‐way analysis of variance, chi‐square ‘likelihood ratio’ tests, and descriptive statistics. The findings of the study provide evidence to the effect that poverty does not cause environmental degradation as the knowledge, attitude, and behaviour of the urban poor concerning solid waste management are found to have been conducive to the environment. The study suggests that the problems of poverty and environment need to be seen differently as the causal relationship between the two does actually depend on the level of socioeconomic profile and the type of environmental practices of a particular group of community

The purpose of this study is twofold: first, to examine the role of non-governmental organizations (NGOs) in increasing customer environmental awareness (CEA) to decrease the municipal solid waste (MSW), and secondly, to examine the effect of government policies in the amount of air pollution caused by transfer stations (TSs).

This study proposes a mixed-integer nonlinear programming model. For solving this multi-objective problem, the authors use epsilon constraint method, which presented eight Pareto solutions. For selecting the best solution, the analytic hierarchy process approach is used. The presented model is applied on a real case study, and the results are discussed and sensitivity analysis is implemented on the parameters of the concern.

This study confirms the assumption that by allocating budget to NGOs for increasing CEA, the produced waste will be decreased.

In the present study, the authors only investigate air pollution caused by TS. Future studies can investigate other types of pollution. Furthermore, uncertainty in the amount of produced waste can be variable making the problem closer to the real environment. In this case, robust optimization may have better results.

Based on the results of sensitivity analysis, some implications obtain that can highlight by managers in the decision-making process. The operational costs of TS have a critical aspect in founding TS, so using new technology and high-tech machines for operational processes of TSs, can result in decreasing the running cost of TSs. Also, the determination of TS capacity is a remarkable issue in optimization, which should be paid special attention to this for the design of TSs in the planning phase of the system. Moreover, collaborating with NGOs has a good effect on increasing CEA that results in a decrease of MSW.

The role of NGOs and government simultaneity has been considered in a green supply chain. Moreover, the authors considered TS between source and disposal that reduce the time of transferring waste. Therefore, this study can be beneficial for the MSW management system, which faces the problems in the lack of capacity and transportation problems and environmental issues by proposing solutions in three studies including economic, environmental and social aspects.

This paper aims to focus on a medical goods distribution problem and pharmacological waste collection by plug-in hybrid vehicles with some real-world restrictions. In this research, considering alternative energy sources and simultaneous pickup and delivery led to a decrease in greenhouse gas emissions and distribution costs, respectively.

Here, this problem has been modeled as mixed-integer linear programming with the traveling and energy consumption costs objective function. The GAMS was used for model-solving in small-size instances. Because the problem in this research is an NP-hard problem and solving real-size problems in a reasonable time is impossible, in this study, the artificial bee colony algorithm is used.

Then, the algorithm results are compared with a simulated annealing algorithm that recently was proposed in the literature. Finally, the results obtained from the exact solution and metaheuristic algorithms are compared, analyzed and reported. The results showed that the artificial bee colony algorithm has a good performance.

In this paper, medical goods distribution with pharmacological waste collection is studied. The paper was focused on plug-in hybrid vehicles with simultaneous pickup and delivery. The problem was modeled with environmental criteria. The traveling and energy consumption costs are considered as an objective function.

This purpose of this paper is concerned with the issue of designing and operating a sustainable waste management system, in rapidly growing urban areas. Some existing models for waste management and the extent to which they could be applied in a specific environment – Cairo for example – are discussed. An integrated framework which can serve as a basis for the development of a sustainable waste management system is proposed. Sustainability of the system, opportunities and challenges, material re-use and recycling, composting, incineration and energy production and land-filling are examined. Relevant waste management and cost sub-models inherent to the system are discussed. In addition, some other environmental and social aspects are also debated. The main focus of this paper is to provide some insights into the design of a more effective and integrated sustainable waste management system applicable for developing economies.

An in-depth analysis is carried out for the existing models and approaches for waste management. This has led to the development of a framework which can be implemented.

A comprehensive conceptual framework for a waste management system is developed. The major inputs and expected outputs are clearly identified.

A comprehensive and complete system for waste management is proposed. This system can be operationalized and implemented with a view of sustainability.

After the 2004 Indian Ocean Tsunami, major resettlement programmes were implemented in the affected countries including Sri Lanka and India. New settlements were built from scratch on vacant land, which consisted of building new houses and provision of infrastructure and services. Some of these programmes in Sri Lanka and India were reviewed in an Australian Research Council (ARC) funded research and this paper presents and analyses some of the findings of the research. The paper aims to discuss these issues.

The research is based on interviews of residents and representatives of agencies involved in planning and implementing the resettlement programmes, and on-site observations. The investigation examined critical aspects of settlement development including site planning, transport, drainage, water supply, sanitation, waste management and security.

Very little site planning guidelines were available specifically for resettlement programmes; in both the case study countries, general planning guidelines were applied. Provision and management of infrastructure and services presents great challenges in developing countries as high capital investment and good technical skills for design, implementation and maintenance are required. Some of the resettlement schemes had the advantage of being centrally located and hence had access to schools, health centres and other facilities. However, others were in isolated locations and beneficiaries faced problems in accessing basic facilities. Drainage was a problem – most schemes did not have any surface drainage plan; low areas had not been elevated, slopes not levelled, and land not compacted before construction. Electricity and water supply had been provided in all the programmes, but conditions and quality varied. In many of the schemes, sanitation presented a problem. However, in Chennai, the sewage system worked well and this was one achievement all interview respondents praised. Solid waste management and security posed additional problems.

In the global context of increasing frequency and intensity of disasters due to climate change, adequate planning and implementation of reconstruction and resettlement programmes has become more important than ever. In this regard, the lessons gained in this paper should be of value and can provide guidance to post-disaster resettlement programmes in developing countries.