A new model for the hazardous waste location-routing problem

Hazardous waste management involves the collection, transportation, treatment and disposal of hazardous wastes. In this paper a new multiobjective location-routing model is proposed. Our model also includes some constraints, which were observed in the literature but were not incorporated into previous models. The aim of the proposed model is to answer the following questions: where to open treatment centers and with which technologies, where to open disposal centers, how to route different types of hazardous waste to which of the compatible treatment technologies, and how to route waste residues to disposal centers. The model has the objective of minimizing the total cost and the transportation risk. A large-scale implementation of the model in the Central Anatolian region of Turkey is presented.     

垃圾焚烧过程自适应模糊复合控制策略

针对垃圾焚烧过程的非线性、时变性和大滞后特性,提出了一种结合蒸汽负荷粗调和炉温偏差细调的自适应模糊复合控制策略。首先根据蒸汽负荷的大小采用模糊PID控制器进行给料量的粗调,然后根据炉温偏差和偏差变化率采用自适应模糊控制器进行给料量的细调,再将两给料输出值相比较,确定出当前给料量变化值。实际运行结果表明,系统控制曲线相对平稳,炉温预报误差基本控制在±20℃以内。该方法为焚烧炉燃烧过程的智能控制提供了新的途径。     

数据驱动的城市固废焚烧过程烟气含氧量预测控制

烟气含氧量的精准控制对城市固废焚烧处理厂的稳定高效运行具有重要意义.然而,由于固废焚烧过程固有的非线性和不确定性,难以实现烟气含氧量的有效控制.为此,文中提出一种数据驱动的城市固废焚烧过程烟气含氧量预测控制方法.首先,设计了一种基于自组织长短期记忆(SOLSTM)网络的预测模型,结合神经元活跃度与显著性动态调整隐含层结构,提高了烟气含氧量的预测精度.其次,为了保证优化效率,利用梯度下降法求解控制律.此外,基于李雅普诺夫理论分析了所提方法的稳定性,确保控制器在实际应用过程中的可靠性.最后,基于实际工业数据对所提出的控制方法进行了验证,结果表明,提出的数据驱动预测控制方法能实现对城市固废焚烧过程烟气含氧量的稳定高效控制.     

The uncapacitated hub location problem in networks under decentralized management

We propose a new hub location model defined by the minimization of costs. The main contribution of this work is to permit the analysis of a hub-and-spoke network operated under “decentralized management”. In this type of network, various transport companies act independently, and each makes its route choices according to its own criteria, which can include cost, time, frequency, security and other factors, including subjective ones. Therefore, due to the diversity of the various companies’ criteria, one can expect that between each origin–destination pair, a fraction of the flow will be carried through hubs and a fraction will be carried by the direct route. to resolve this problem, it becomes necessary to determine the probability that any network user will choose the hub route for each trip to be made (or for each load to be carried). We present an integer programming formulation, subject the new model to experiments with an intermodal general cargo network in Brazil and address questions regarding the solution of the problem in practice.     

Computer-based interface for an integrated solid waste management optimization model

Planning a regional waste management strategy is a critical step that, if not properly addressed, will lead to an inefficient integrated solid waste management (ISWM) system. Regional planning affects the design, implementation, and efficiency of the overall ISWM scheme. Consequently, decision-makers must look for optimized regional waste management planning to achieve a successful strategy. The optimization of an ISWM strategy for an area requires the knowledge of available solid waste management alternatives and technologies, economic and environmental costs associated with these alternatives, and their applicability to the specific area. Decision-makers often have to rely on optimization models to examine the impacts of mass balance, capacity limitations, operation, and site availability as well as to analyze different alternative options in the selection of a cost effective, environmentally sound waste management alternative. In this context, the complexity associated with the formulation of optimization models may hinder its use, and consequently, user friendliness is a major concern. This paper presents an interface that was developed to address this concern, that is to formulate the matrices associated with an integrated waste management optimization model.     

考虑公众风险的多目标医疗废物选址路径问题及樽海鞘算法求解

针对医疗废物处理中心的选址路径问题,在考虑公众风险的情况下,构建多目标优化模型。首先,分别从政府、公众和处理中心承包商角度出发,构建了以运营成本、风险成本以及运输成本最小化的多目标选址路径模型;其次,针对所构建模型的特点,设计了一种改进的多目标樽海鞘算法对模型进行求解;最后,以四川省成都市的医疗废物处理中心的规划项目为例,对构建的模型和算法进行验证,通过优化结果的对比分析,验证了模型的可行性和算法的有效性。     

Fuzzy parametric programming model for multi-objective integrated solid waste management under uncertainty

Solid waste management is increasingly becoming a challenging task for the municipal authorities due to increasing waste quantities, changing waste composition, decreasing land availability for waste disposal sites and increasing awareness about the environmental risk associated with the waste management facilities. The present study focuses on the optimum selection of the treatment and disposal facilities, their capacity planning and waste allocation under uncertainty associated with the long-term planning for solid waste management. The fuzzy parametric programming model is based on a multi-objective, multi-period system for integrated planning for solid waste management. The model dynamically locates the facilities and allocates the waste considering fuzzy waste quantity and capacity of waste management facility. The model addresses uncertainty in waste quantity as well as uncertainties in the operating capacities of waste management facilities simultaneously. It was observed that uncertainty in waste quantity is likely to affect the planning for waste treatment/disposal facilities more as compared with the uncertainty in the capacities of the waste management facilities. The relationship between increase in waste quantity and increase in the total cost/risk involved in waste management is found to be nonlinear. Therefore, it is possible that a marginal change in waste quantity could increase the total cost/risk substantially. The information obtained from the analysis of modeling results can be effectively used for understanding the effect of changing the priorities and objectives of planning decisions on facility selections and waste diversions.     

A multiple-criteria decision problem for optimal management of farm resources under uncertainty - a case study

An attempt is made to minimize the total operational cost and specific energy for rice cultivation, when the constraints relating to the availability of power sources and crop yield are supposed to be stochastic in nature. The Sequential Linear Goal Programming algorithm has been used to solve the resulting multiple objective optimization problem.     

A variable neighborhood descent algorithm for a real waste collection problem with mobile depots

We consider a waste collection problem encountered in Due Carrare, a town located in Northern Italy. The original feature of the problem consists in the need for arranging appointments between vehicles along their routes so that small vehicles can dump their contents in the large ones and continue their work. This feature identifies the problem as a generalization of the well‐known Capacitated Arc Routing Problem (CARP). We propose a local search heuristic obtained from a variable neighborhood procedure suggested by Hertz and Mittaz (2001) for the CARP. In the Due Carrare instance, the proposed algorithm decreases the total route duration, apart from the required time for any feasible set of routes, of about 30% with respect to the routes so far adopted.     

Orchestrating big data analytics capability for sustainability: A study of air pollution management in China

Under rapid urbanization, cities are facing many societal challenges that impede sustainability. Big data analytics (BDA) gives cities unprecedented potential to address these issues. As BDA is still a new concept, there is limited knowledge on how to apply BDA in a sustainability context. Thus, this study investigates a case using BDA for sustainability, adopting the resource orchestration perspective. A process model is generated, which provides novel insights into three aspects: data resource orchestration, BDA capability development, and big data value creation. This study benefits both researchers and practitioners by contributing to theoretical developments as well as by providing practical insights.     

A software solution for environmental information: A case study on waste management

The extent and complexity of environmental data management needs have increased significantly over the past several years. As environmental regulations increase, and compliance solutions are evaluated, the need to monitor and document performance becomes increasingly important. Regulatory complexities and volumes of monitoring data mandate the use of detailed procedures to assure compliance with accounting for wastes produced and disposed. A commercially available comprehensive environmental data management system offers a solution, particularly in times when personnel availability for in-house software development is limited. The modular ECOTRACtm⁽¹⁾ system enables users to customize a system to their data management needs. Based on dBASE IIItm⁽²⁾, the system offers the flexibility to meet specific needs without extensive programming or computer knowledge. Standard reports allow consistent and timely reporting to management and regulatory authorities. Case studies demonstrate efficiencies gained through use of commercially available environmental data management software for microcomputers. ECOTRACtm software has proven useful to a variety of industry applications, and has been favorably received by independent technical reviewers.     

Developing an integrated solid waste management system in western Greece: a dynamic location analysis

We study the problem of the simultaneous design of a distribution network with central treatment facilities, transfer stations and landfills, and the coordination of waste flows within this network for a long-term planning horizon. We apply these concepts in a research project for the development of a solid waste management system for a specific region in Greece. We then formulate a dynamic mixed integer programming model that minimizes the sum of costs for opening facilities and variable transportation costs related to solid waste flows. Finally, we analyze the results of the model and evaluate the various technologies that may be implemented in the treatment facilities.     

Operations research in solid waste management: A survey of strategic and tactical issues

Solid waste management (SWM) is an increasingly complex task, absorbing a huge amount of resources and having a major environmental impact. Computerized systems based on operations research techniques can help decision makers to achieve remarkable cost savings as well as to improve waste recovery. Nevertheless, the literature is quite scattered and disorganized. The objective of this paper is to present an updated survey of the most relevant operations research literature on SWM, mainly focusing on strategic and tactical issues. In addition to providing an extensive bibliographic coverage, we describe the relationships between the various problems, and outline future research.     

A generalized multistage optimization modeling framework for life cycle assessment-based integrated solid waste management

Solid waste management (SWM) is an integral component of civil infrastructure and the global economy, and is a growing concern due to increases in population, urbanization, and economic development. In 2011, 1.3 billion metric tons of municipal solid waste (MSW) were generated, and this is expected to grow to 2.2 billion metric tons by 2025. In the U.S., MSW systems processed approximately 250 million tons of waste and produced 118 Tg of CO₂e emissions, which represents over 8% of non-energy related greenhouse gas (GHG) emissions, and 2% of total net GHG emissions. While previous research has applied environmental life cycle assessment (LCA) to SWM using formal search techniques, existing models are either not readily generalizable and scalable, or optimize only a single time period and do not consider changes likely to affect SWM over time, such as new policy and technology innovation. This paper presents the first life cycle-based framework to optimize—over multiple time stages—the collection and treatment of all waste materials from curb to final disposal by minimizing cost or environmental impacts while considering user-defined emissions and waste diversion constraints. In addition, the framework is designed to be responsive to future changes in energy and GHG prices. This framework considers the use of existing SWM infrastructure as well as the deployment and utilization of new infrastructure. Several scenarios, considering cost, diversion, and GHG emissions, are analyzed in a 3-stage test system. The results show the utility of the multi-stage framework and the insights that can be gained from using such a framework. The framework was also used to solve a larger SWM system; the results show that the framework solves in reasonable time using typical hardware and readily available mathematical programming solvers. The framework is intended to inform SWM by considering costs, environmental impacts, and policy constraints.     

解决移动计算位置管理问题的差分进化算法

提出了一种解决位置管理问题的差分进化算法,给出了一种将采用浮点编码的种群个体映射为问题解的方法、基于问题特性的种群初始化启发式方法,以及早熟收敛问题的解决策略.基于随机生成的数据对算法进行了模拟实验,将该算法的结果与遗传算法、禁忌搜索算法及蚁群算法进行了对比.     

Collaborative virtual geographic environments: A case study of air pollution simulation

The integration of high dimensional geo-visualization, geo-data management, geo-process modeling and computation, geospatial analysis, and geo-collaboration is a trend in GIScience. The technical platform that matches the trend forms a new framework unlike that of GIS and is conceptualized in this paper as a collaborative virtual geographic environment (CVGE). This paper focuses on two key issues. One is scientific research on CVGE including the concept definition and the conceptual and system framework development. The other is a prototype system development according to CVGE frameworks for air pollution simulation in the Pearl River Delta. The prototype system integrates air pollution source data, air pollution dispersion models, air pollution distribution/dispersion visualization in geographically referenced environments, geospatial analysis, and geo-collaboration. Using the prototype system, participants from geographically distributed locations can join in the shared virtual geographic environment to conduct collaborative simulation of air pollution dispersion. The collaborations supporting this simulation happen on air pollution source editing, air pollution dispersion modeling, geo-visualization of the output of the modeling, and geo-analysis.     

Continuous-discrete simulation-based decision making framework for solid waste management and recycling programs

Solid waste produced as a by-product of our daily activities poses a major threat to societies as populations grow and economic development advances. Consequently, the effective management of solid waste has become a matter of critical importance for communities. However, solid waste management systems are inherently large-scale, diverse, and subject to many uncertainties, and must serve numerous stakeholders with divergent objectives. In this study, we propose a simulation-based decision-making and optimization framework for the analysis and development of effective solid waste management and recycling programs. The proposed solution includes a database and two main modules: an assessment module and a resource allocation optimization module. The assessment module identifies the sources of uncertainties in the system, which are then parameterized and incorporated into the resource allocation optimization module. The resource allocation optimization module involves a novel discrete–continuous model of the system under consideration, in which the continuous nature of decision variables is maintained while inherently discrete processing and transfer operations are accurately captured. The model operates with respect to the waste types and characteristics, costs, environmental impacts, types, location and capacities of processing facilities, and their technological capabilities. Then, an optimization mechanism embedded in the resource allocation optimization module solves the multi-criteria problem of the allocation of limited resources by simultaneously optimizing all relevant decision variables, evaluating performance in real-time via the model. Here, the optimum solution is considered as the combination of parameters that will lead to the highest recycling rate with minimum cost. The proposed framework has been successfully demonstrated for the Miami-Dade County Solid Waste Management System in the State of Florida.     

SWAMI: An autonomous mobile robot for inspection of nuclear waste storage facilities

The Stored Waste Autonomous Mobile Inspector (SWAMI) is a prototype mobile robot designed to perform autonomous inspection of nuclear and hazardous waste storage facilities. The onboard control system, consisting of three Motorola 68030-based microcomputers, controls a number of subsystem components including barcode readers, cameras, and a radiation detector. The control system software, running under the VxWorks real-time operating system, is designed toward the client-server model and is implemented in C++. GENISAS, a communication library developed by the Sandia National Laboratories, is used extensively. Much of the onboard software was generated by a custom code generation tool called Moses.     

二级垃圾回收中转设施选址问题的降阶回溯算法

随着我国城市化进程的加快和经济的高速发展,城市中因生产生活所产生的垃圾废料量日益增加,如何有效地建立回收中转设施是当前社会需要解决的问题。对二级垃圾回收设施选址问题进行研究,其实质为组合优化中的NP-hard问题。首先根据实际情况对二级垃圾回收中转设施选址问题进行数学建模,研究该问题的数学性质并给予证明,利用这些性质减小问题规模,降低求解难度;然后设计符合该问题的分配子算法、上下界子算法,基于以上算法提出一种可以在减小问题规模的同时得到精确解的降阶回溯算法;最后通过分析和模拟若干个示例进一步阐述该算法的原理及执行过程,结果表明该算法能通过减小问题规模,降低问题求解的难度。     

解决移动计算位置管理的离散差分进化算法

位置管理问题是移动计算环境中的一个重要问题。提出了一种解决位置管理问题的离散差分进化算法,给出了种群的离散编码方法和一种新的变异操作机制,提出了基于问题特性的种群初始化启发式方法,以及早熟收敛问题的解决策略。基于随机生成的数据对算法进行了模拟实验,将该算法的结果与遗传算法、禁忌搜索算法及蚁群算法进行了对比。