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The multi-decision support model is developed and demontrated to minimise the cost of transport and treatment of municipal solid waste under the effected of socio and environment. The tool is simple, easy to upgrade to fit with the local condition, easy and fast running (some minutes). The model is used to compare the operation of MSW system if there are some changes in impact factors. The results of model show: (1) the distribution of amount of MSW from sources to treatment plants, (2) the selected treatment technologies, its capacity and location, (3) cost analysis of transport, treatment of MSW and the income. In the current situation of HCMC (case study 2), the model proposed 2 treatment tecnologies in 20 years planning, called bath anaerobic digestion technology and bioreactor landfill, with the treatment amount of 70% and 30%, respectively. In case of the planned land for treatment zone is not reached as case study 2, incineration technology will be a good choice.

Summary For the last two decades, food logistics systems have seen the transition from traditional Logistics Management (LM) to Food Logistics Management (FLM), and successively, to Sustainable Food Logistics Management (SFLM). Accordingly, food industry has been subject to the recent challenges of reducing the amount of food waste and raising energy efficiency to reduce greenhouse gas emissions. These additional challenges add to the complexity of logistics operations and require advanced decision support models which can be used by decision makers to develop more sustainable food logistics systems in practice. Hence, the overall objective of this thesis was to obtain insight in how to improve the sustainability performance of food logistics systems by developing decision support models that can address the concerns for transportation energy use and consequently carbon emissions, and/or product waste, while also adhering to competitiveness. In line with this overall objective, we have defined five research objectives. The first research objective (RO), which is to identify key logistical aims, analyse available quantitative models and point out modelling challenges in SFLM, is investigated in Chapter 2. In this chapter, key logistical aims in LM, FLM and SFLM phases are identified, and available quantitative models are analysed to point out modelling challenges in SFLM. A literature review on quantitative studies is conducted and also qualitative studies are consulted to better understand the key logistical aims and to identify the relevant system scope issues. The main findings of the literature review indicate that (i) most studies rely on a completely deterministic environment, (ii) the food waste challenge in logistics has not received sufficient attention, (iii) traveled distance is often used as a single indicator to estimate related transportation cost and emissions, and (iv) most studies propose single objective models for the food logistics problems. This chapter concludes that new and advanced quantitative models are needed that take specific SFLM requirements from practice into consideration to support business decisions and capture food supply chain dynamics. These findings motivated us to work on the following research objectives RO2, RO3, RO4 and RO5. RO2, which is to analyse the relationship between economic (cost) and environmental (transportation carbon emissions) performance in a network problem of a perishable product, is investigated in Chapter 3. This chapter presents a multi-objective linear programming (MOLP) model for a generic beef logistics network problem. The objectives of the model are (i) minimizing total logistics cost and (ii) minimizing total amount of greenhouse gas emissions from transportation operations. The model is solved using the e-constraint method. This study breaks away from the literature on logistics network models by simultaneously considering transportation emissions (affected by road structure, vehicle and fuel types, weight loads of vehicles, traveled distances), return hauls and product perishability in a MOLP model. We present computational results and analyses based on the application of the model to a real-life international beef logistics chain operating in Nova Andradina, Mato Grosso do Sul, Brazil, and exporting beef to the European Union. Trade-off relationships between multiple objectives are observed by the derived Pareto frontier that presents the cost of being sustainable from the point of reducing transportation emissions. The results indicate the importance of distances between actors in terms of environmental impact. Moreover, sensitivity analysis on important practical parameters show that export ports' capacities put pressure on the logistics system; decreasing fuel efficiency due to the bad infrastructure has negative effects on cost and emissions; and green tax incentives result in economic and environmental improvement. RO3, which is to investigate the performance implications of accommodating explicit transportation energy use and traffic congestion concerns in a two-echelon capacitated vehicle routing problem (2E-CVRP), is investigated in Chapter 4. The multi-echelon distribution strategy in which freight is delivered to customers via intermediate depots rather than using direct shipments is an increasingly popular strategy in urban logistics. Its popularity is primarily due to the fact that it alleviates the environmental (e.g., energy usage and congestion) and social (e.g., traffic-related air pollution, accidents and noise) consequences of logistics operations. This chapter presents a comprehensive mixed integer linear programming formulation for a time-dependent 2E-CVRP that accounts for vehicle type, traveled distance, vehicle speed, load, multiple time zones and emissions. A case study in a supermarket chain operating in the Netherlands shows the applicability of the model to a real-life problem. Several versions of the model, each differing with respect to the objective function, are tested to produce a number of selected Key Performance Indicators (KPIs) relevant to distance, time, fuel consumption and cost. This chapter offers insight in the economies of environmentally-friendly vehicle routing in two-echelon distribution systems. The results suggest that an environmentally-friendly solution is obtained from the use of a two-echelon distribution system, whereas a single-echelon distribution system provides the least-cost solution. RO4, which is to investigate the performance implications of accommodating explicit transportation energy use, product waste and demand uncertainty concerns in an inventory routing problem (IRP), is investigated in Chapter 5. Traditional assumptions of constant distribution costs between nodes, unlimited product shelf life and deterministic demand used in the IRP literature restrict the usefulness of the proposed models in current food logistics systems. From this point of view, our interest in this chapter is to enhance the traditional models for the IRP to make them more useful for decision makers in food logistics management. Therefore, we present a multi-period IRP model that includes truck load dependent (and thus route dependent) distribution costs for a comprehensive evaluation of CO2 emission and fuel consumption, perishability, and a service level constraint for meeting uncertain demand. A case study on the fresh tomato distribution operations of a supermarket chain shows the applicability of the model to a real-life problem. Several variations of the model, each differing with respect to the considered aspects, are employed to present the benefits of including perishability and explicit fuel consumption concerns in the model. The results suggest that the proposed integrated model can achieve significant savings in total cost while satisfying the service level requirements, and thus offers better support to decision makers. RO5, which is to analyse the benefits of horizontal collaboration in a green IRP for perishable products with demand uncertainty, is investigated in Chapter 6. This chapter presents a decision support model, which includes a comprehensive evaluation of CO2 emission and fuel consumption, perishability, and a service level constraint for meeting uncertain demand, for the IRP with multiple suppliers and customers. The model allows to analyse the benefits of horizontal collaboration in the IRP with respect to several KPIs, i.e., total emissions, total driving time, total routing cost comprised of fuel and wage cost, total inventory cost, total waste cost, and total cost. A case study on the distribution operations of two suppliers, where the first supplier produces figs and the second supplier produces cherries, shows the applicability of the model to a real-life problem. The results show that horizontal collaboration among the suppliers contributes to the decrease of aggregated total cost and emissions in the logistics system, whereas the obtained gains are sensitive to the changes in parameters such as supplier size or maximum product shelf life. According to the experiments, the aggregated total cost benefit from cooperation varies in a range of about 4-24% and the aggregated total emission benefit varies in a range of about 8-33%. Integrated findings from Chapters 2, 3, 4, 5 and 6 contribute to the SFLM literature by (i) reflecting the state of the art on the topic of quantitative logistic models which have sustainability considerations, (ii) providing decision support models which can be used by decision makers to improve the performance of the sustainable food logistics systems in terms of logistics cost, transportation energy use and carbon emissions, and/or product waste, and (iii) presenting the applicability of the proposed models in different case studies based on mainly real data, multiple scenarios, and analysis. The developed decision support models exploit several logistics improvement opportunities regarding transportation energy use and emissions, and/or product waste to better aid SFLM, as distinct from their counterparts in literature. To conclude, the case study implementations in this thesis demonstrate that (i) perishability and explicit consideration of fuel consumption are important aspects in logistics problems, and (ii) the provided decision support models can be used in practice by decision makers to further improve sustainability performance of the food logistics systems.

Summary of the thesis titled “Sustainable Reverse Logistics for Household Plastic Waste” PhD Candidate: Xiaoyun Bing Recycled plastic can be used in the manufacturing of plastic products to reduce the use of virgin plastics material. The cost of recycled plastics is usually lower than that of virgin plastics. Therefore, it is environmentally and economically beneficial to improve the plastic recycling system to ensure more plastic waste from households is properly collected and processed for recycling. Plastic waste has a complex composition and is polluted, thus requires a substantial technical effort to separate the plastics from the waste and to sort these into recyclable materials. There are several alternatives in the existing collection methods (curb-side and drop-off) and separation methods (source separation and post-separation). It is challenging to select a suitable combination of these methods and to design a network that is efficient and sustainable. It is necessary to build a suitable, efficient and sustainable recycling network from collection to the final processor in order to provide solutions for different future scenarios of plastics household waste recycling. Decision support is needed in order to redesign the plastic waste reverse logistics so that the plastic waste recycling supply chain can be improved towards a more sustainable direction. To improve the efficiency in the recycling of plastic packaging waste, insights are required into this complex system. Insights solely on a municipal level are not sufficient, as the processing and end market are important for a complete network configuration. Therefore, we have investigated the problem at three levels: municipal, regional, and global. Decision support systems are developed based on optimization techniques to explore the power of mathematical modelling to assist in the decision-making process. This thesis investigates plastic waste recycling from a sustainable reverse logistics angle. The aim is to analyse the collection, separation and treatments systems of plastic waste and to propose redesigns for the recycling system using quantitative decision support models. We started this research project by identifying research opportunities. This was done through a practical approach that aimed to find future research opportunities to solve existing problems (Chapter 2). We started from a review of current municipal solid waste recycling practices in various EU countries and identified the characteristics and key issues of waste recycling from waste management and reverse logistics point of view. This is followed by a literature review regarding the applications of operations research. We conclude that waste recycling is a multi-disciplinary problem and that research opportunities can be found by considering different decision levels simultaneously. While analyzing a reverse supply chain for Municipal Solid Waste (MSW) recycling, a holistic view and considering characteristics of different waste types are necessary. Municipal Level In Chapter 3, we aim to redesign the collection routes of household plastic waste and compare the collection options at the municipal level using eco-efficiency as a performance indicator. The collection problem is modeled as a vehicle routing problem. A tabu search heuristic is used to improve the routes. Scenarios are designed according to the collection alternatives with different assumptions in collection method, vehicle type, collection frequency, and collection points, etc. The results show that the source-separation drop-off collection scenario has the best performance for plastic collection, assuming householders take the waste to the drop-off points in a sustainable manner. In Chapter 4, we develop a comprehensive cost estimation model to further analyze the impacts of various taxation alternatives on the collection cost and environmental impact. This model is based on such variables as fixed and variable costs per vehicle, personnel cost, container or bag costs, as well as emission costs (using imaginary carbon taxes). The model can be used for decision support when strategic changes to the collection scheme of municipalities are considered. The model, which considers the characteristics of municipalities, including degree of urbanization and taxation schemes for household waste management, was applied to the Dutch case of post-consumer plastic packaging waste. The results showed that post-separation collection generally has the lowest costs. Curb-side collection in urban municipalities without residual waste collection taxing schemes has the highest cost. These results were supported by the conducted sensitivity analysis, which showed that higher source-separation responses are negatively related to curb-side collection costs. Regional Level Chapter 5 provides decision support for choosing the most suitable combination of separation methods in the Netherlands. Decision support is provided through an optimized reverse logistics network design that makes the overall recycling system more efficient and sustainable, while taking into account the interests of various stakeholders (municipalities, households, etc.). A mixed integer linear programming (MILP) model, which minimizes both transportation cost and environmental impact, is used to design this network. The research follows the approach of a scenario study; the baseline scenario is the current situation and other scenarios are designed with various strategic alternatives. Comparing these scenarios, the results show that the current network settings of the baseline situation is efficient in terms of logistics, but has the potential to adapt to strategic changes, depending on the assumptions regarding availability of the required processing facilities to treat plastic waste. In some of the tested scenarios, a separate collection channel for polyethylene terephthalate (PET) bottles is cost-efficient and saves carbon emission. Although the figures differ depending on the choices in separation method made by municipalities, our modeling results of all the tested scenarios show a reduction in carbon emissions of more than 25 percent compared to the current network. Chapter 6 studies a plastic recycling system from a reverse logistics angle and investigates the potential benefits of a multimodality strategy to the network design of plastic recycling. The aim was to quantify the impact of multimodality in the network in order to provide decision support for the design of more sustainable plastic recycling networks in the future. A MILP model is developed in order to assess different plastic waste collection, treatment, and transportation scenarios. A baseline scenario represents the optimized current situation, while other scenarios allow multimodality options (barge and train) to be applied. With our input parameter settings, results show that transportation costs contribute to approximately 7 percent of the total costs, and multimodality can help reduce transportation costs by almost 20 percent (CO_2-eq emissions included). In our illustrative case with two plastic separation methods, the post-separation channel benefits more from a multimodality strategy than the source-separation channel. This relates to the locations and availability of intermediate facilities and the quantity of waste transported on each route. Global Level After the regional network redesign, Chapter 7 shows a global network redesign. The aim of this chapter was to redesign a reverse supply chain from a global angle based on a case study conducted on household plastic waste distributed from Europe to China. Emissions trading restrictions are set on processing plants in both Europe and China. We used a mixed-integer programming model in the network optimization to decide on location reallocation of intermediate processing plants under such restrictions, with the objective of maximizing total profit under Emission Trading Schemes (ETS). Re-locating facilities globally can help reduce the total cost. Once carefully set, ETS can function well as incentive to control emissions in re-processors. Optimization results show that relocating re-processing centers to China reduces total costs and total transportation emissions. ETS applied to re-processors further helps to reduce emissions from both re-processors and the transportation sector. Carbon caps should be set carefully in order to be effective. These results give an insight in the feasibility of building a global reverse supply chain for household plastic waste recycling and demonstrate the impact of ETS on network design. The results also provide decision support for increasing the synergy between the policy for global shipping of waste material and the demand of recycled material. Conclusions Chapter 8 summarizes the findings from chapters 2 to 7 and provides brief answers to the research questions. Beyond that, the integrated findings combine the results from different decision levels and elaborate the impacts of various system characteristics and external factors on the decision making in order to achieve an improved sustainable performance. Main findings are: Regarding the impact of carbon cost, the results from different chapters are consistent in terms that emission cost is only a small part of the total cost, even when carbon cost is set at its historically highest figure. When carbon price is set to a different value, impact of carbon cost on the change of optimization results is higher on the upstream of the reverse supply chain for plastic waste than the downstream.In Emission Trading scheme (ETS), carbon cap has a larger impact on eco-efficiency performance of the global network than carbon price.On one decision level, models can help to find the ``best option". For example, in the collection phase, the average total collection costs per ton of plastic waste collected for source-separation municipalities are more than twice of the post-separation municipalities' collection costs due to the frequent stops made and idling time at each stop. From the regional network perspective, post-separation scenarios have higher costs and environmental impact than source separation due to the limited number of separation centers compared to the numerous cross-docking sites for source-separation. When combining decision levels, however, it is difficult to find one ``best option" that fits all, as there are contradictory results when looking at the same factor from different decision levels. Through decision support models, we provided clear insights into the trade-offs and helped to quantify the differences and identify key factors to determine the differences.Population density differences in various municipalities influence the performance of curbside collection more than drop-off collection. This information is valuable for decision makers to consider in the decision making process. Finally, managerial insights derived from sustainable reverse logistics for household plastic waste are summarized in conclusion section.

The aim of this thesis is to enable taking more sustainable and cost-effective decisions on MSW management in developing cities. For this purpose, a tool named SURMAT was developed and applied using data of Ho Chi Minh City, Viet Nam (chapter 6). In order to prepare the tool for modeling of the MSW management in Ho Chi Minh City, an analysis of the current MSW management system (chapter 2), a selection of technologies (chapter 3, 4) and a costs analysis of the selected technologies (chapter 5) have been conducted. Various possible solid waste management strategies for Ho Chi Minh City for period of twenty years were elaborated and discussed focusing on minimization of costs and maximization of electricity production from wastes (chapters 6 and 7). SURMAT supports in a systematic way the optimization of logistics and choice of treatment technologies in dependence of specific situation-bound constraints, such as land availability and production of useful products from wastes. SURMAT is simple to operate and well adaptable to new situations. It can help to generate guidelines or master plans for urban solid waste management. The methodology applied to develop this decision support tool can be used to set up other tools for MSW management or for other domains.