Theoretical model and implementation of a real time intelligent bin status monitoring system using rule based decision algorithms

Due to the rising trend of urbanization along with overconsumption of non-recyclable resources, the volume of municipal solid waste is increasing every day. An efficient, cost effective and environment friendly solution for real time bin status monitoring, collection and transportation of municipal solid waste is still a major challenge to the local municipal authorities. This research proposes a novel model, architecture and intelligent sensing algorithm for real time solid waste bin monitoring system that would contribute to the solid waste collection optimization. The monitoring application is based on decision algorithms for sensing solid waste data in a wireless sensor network. The system is built on a three level architecture like smart bin, gateway and control station. The elementary concept is that, smart bins collect their status when any changes occur and transmit the status data to a server via an intermediate coordinator. A set of applications in server presents the updated bin status on real time. The field test performances show that the system can efficiently monitor real time bin status that makes it feasible to decide, which bin should collect and which should not. Thus the proposed system has achieved its goal to provide real time bin status information to the solid waste management operator. Later, this information can be used for collection route optimization to reduce collection costs and carbon emissions which in turn contribute to build green society.     

基于GIS的城市生活垃圾收运管理系统

针对城市生活垃圾快速增长所带来的收运成本增加以及居民生活环境恶化等问题,提出基于地理信息系统(GIS)的垃圾收运管理系统设计方案,包括系统结构、数据库模型等,采用扫描与分支定界相结合的算法实现垃圾收运的调度优化。选择某地区的一部分收运线路进行实验,结果表明,系统能方便有效地进行垃圾管理并减少收运成本。     

Improved route planning and scheduling of waste collection and transport

The collection of waste is a highly visible and important municipal service that involves large expenditures. Waste collection problems are, however, one of the most difficult operational problems to solve. This paper describes the optimization of vehicle routes and schedules for collecting municipal solid waste in Eastern Finland. The solutions are generated by a recently developed guided variable neighborhood thresholding metaheuristic that is adapted to solve real-life waste collection problems. Several implementation approaches to speed up the method and cut down the memory usage are discussed. A case study on the waste collection in two regions of Eastern Finland demonstrates that significant cost reductions can be obtained compared with the current practice.     

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.     

垃圾分类收运路径问题的新型混合蚁群算法求解

针对垃圾分类收运路径问题,考虑车辆装载容量约束、硬时间窗约束、装载率对成本的影响等条件下,以最小化运输成本和车辆固定成本为目标建立了数学模型。将考虑时间吻合度因子和车容量利用率因子的改进蚁群算法与混沌电磁场优化算法进行动态融合,并结合2-opt和两点交换的局部搜索方法,提出一种以改进蚁群算法为外部框架,混沌电磁场优化算法为内部模块的新型混合蚁群算法对城市生活垃圾分类收运问题进行求解。根据算法间优势互补的思想,利用两种算法的优点来弥补单个算法的缺陷,使其成功应用于该问题。最后,用车辆路径问题标准测试集和上海市杨浦区的数据作为实例进行测试与对比,验证了模型的正确性以及算法的有效性与优化能力。     

Waste collection vehicle routing problem with time windows

In this paper, we address a real life waste collection vehicle routing problem with time windows (VRPTW) with consideration of multiple disposal trips and drivers’ lunch breaks. Solomon's well-known insertion algorithm is extended for the problem. While minimizing the number of vehicles and total traveling time is the major objective of vehicle routing problems in the literature, here we also consider the route compactness and workload balancing of a solution since they are very important aspects in practical applications. In order to improve the route compactness and workload balancing, a capacitated clustering-based waste collection VRPTW algorithm is developed. The proposed algorithms have been successfully implemented and deployed for the real life waste collection problems at Waste Management, Inc. A set of waste collection VRPTW benchmark problems is also presented in this paper.Waste collection problems are frequently considered as arc routing problems without time windows. However, that point of view can be applied only to residential waste collection problems. In the waste collection industry, there are three major areas: commercial waste collection, residential waste collection and roll-on-roll-off. In this paper, we mainly focus on the commercial waste collection problem. The problem can be characterized as a variant of VRPTW since commercial waste collection stops may have time windows. The major variation from a standard VRPTW is due to disposal operations and driver's lunch break. When a vehicle is full, it needs to go to one of the disposal facilities (landfill or transfer station). Each vehicle can, and typically does, make multiple disposal trips per day. The purpose of this paper is to introduce the waste collection VRPTW, benchmark problem sets, and a solution approach for the problem. The proposed algorithms have been successfully implemented and deployed for the real life waste collection problems of Waste Management, the leading provider of comprehensive waste management services in North America with nearly 26,000 collection and transfer vehicles.     

基于智能垃圾桶的垃圾分类动态收运路径优化问题研究

针对城市生活垃圾分类收运过程中存在的环境二次污染和垃圾产生量不确定性等问题,提出了一种基于智能垃圾桶的动态收运车辆路径优化方法。建立以最小化碳排放成本、燃油消耗成本、固定成本和车辆延迟到达惩罚成本为目标的动态车辆路径优化模型。采用滚动时域的方式将动态问题转换为一系列静态问题,并设计两阶段算法进行求解。首先采用粒子群算法对收运车辆路径进行规划,而后在每个时域末,综合考虑待清运垃圾桶的位置和垃圾量、垃圾收运车辆的位置和装载量以动态调整现有车辆路径。研究结果表明,相较于传统的静态收运方案,动态垃圾收运方案能够在降低车辆运输成本和碳排放成本的同时,显著降低由于清运不及时造成的环境二次污染的风险。     

基于PKI机制优化的无线网络认证协议

为了提高无线网络环境中PKI认证的效率,引入可信证书验证代理(TCVP)和证书有效性凭据(CVT)等概念,对PKI认证机制进行了优化,并在此基础上设计了无线认证协议.该协议中,TCVP基于PKI机制对无线网络节点(WN)进行身份认证并为其签发CVT.WN仅需出示CVT即可证明其身份.该协议不但避免了在移动无线终端中执行公钥证书的在线验证操作,还减少了认证协议的消息数.与SSL和WTLS的对比分析结果表明,该协议的传输开销和计算开销更小.     

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.     

A Stackelberg game model for construction waste transportation

The transportation of construction and demolition waste (CDW) is an essential problem in waste management. The CDW generated in large construction projects is typically transported by designated trucks. However, the disposal of scattered CDW produced by individuals or small projects is typically not planned, leading to its illegal dumping. Hong Kong aims to recycle scattered CDW by an appointment-recycling mechanism that involves a three-layered transportation network consisting of construction sites, recycling locations, and disposal facilities. In this study, we develop a two-stage Stackelberg game model to minimize the social costs of this three-layered transportation network. In the first stage, we consider the optimal decisions regarding the recycling locations, assigned trucks, and transport routes from the perspective of the government. In the second stage, the delivery routes for small projects are identified based on the government decisions. We transform the proposed model into a single-level integer program (IP) and conduct numerical experiments to demonstrate its efficiency and effectiveness. To the best of our knowledge, this is the first study to focus on the collection of scattered CDW. Thus, our study contributes to the literature on CDW transportation. Moreover, this study helps address a practical problem, i.e., the illegal dumping of scattered CDW, which is a common concern in many cities. In particular, even small amounts of CDW must be appropriately treated because it may contain hazardous materials.     

An integrated inbound logistics mode with intelligent scheduling of milk-run collection,drop and pull delivery and LNG vehicles

Although it provides a feasible inbound logistics solution for steady production and low inventory management, the Milk-run mode inevitably leads to a high transportation costs due to the features of small-batch and high-frequency delivery. In order to break through the defections of the existing inbound logistics mode, an integrated inbound logistics (IIL) mode with low-carbon and high efficiency is established. An intelligent scheduling method combines Milk-run collection with drop and pull delivery together. Moreover, the LNG vehicles are simultaneously used in the whole process. With AJ company’s auto-parts inbound logistics as a case, the IIL mode is formulated with a mixed integer mathematical model. The genetic algorithm coded with Matlab is used to find the optimal solution. The results show that when compared with the original Milk-run mode, the IIL mode brings massive reductions in driving mileage, wait time and waste gas emission. It can make significant benefits in both economic and social sense. Therefore, it is entirely reasonable for management of industries to believe that the IIL mode will be a feasible and promising alternative for inbound logistics.

     

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.     

A breakable multi-item multi stage solid transportation problem under budget with Gaussian type-2 fuzzy parameters

This paper is based on two mathematical models for multi-item multi-stage solid transportation problem with budget on total transportation cost in Gaussian type-2 fuzzy environment considering the fixed opening charge and operating cost in distribution center. The first model is about transportation of breakable/damageable items, and the second one considers non breakable/damageable items. The main aspect here is to develop the mathematical formulation of multi stage related solid transportation problem where several items are available for transportation. In order to deal with the Gaussian type-2 fuzziness, two chance-constrained programming models are developed based on generalized credibility measures for the objective function as well as the constraints sets with the help of the CV-based reductions method. Finally the reduced model is turned into its equivalent parametric programming problem. The problem is of high complexity and is difficult to find the optimal solution by any classical method and hence a time and space based meta-heuristic Genetic Algorithm has been proposed. Also the equivalent crisp models are solved using GA and LINGO 13.0 and after comparison, GA results are better. The proposed models and techniques are finally illustrated by providing numerical examples. Some sensitivity analysis and particular cases are presented and discussed. Degrees of efficiency is also evaluated for both the techniques.     

分布权值调节概率标准差的文本分类方法

针对文本分类问题,基于特征分布评估权值调节特征概率标准差设计了一种无须特征选择的高效的线性文本分类器。该算法的基本思路是使用特征概率标准差量化特征在文档类中的离散度,并作为特征的基础权重,同时以后验概率的Beta分布函数为基础,运用概率确定性密度函数,评估特征在类别中的分布信息得到特征分布权值,将其调节基础权重得到特征权重,实现了线性文本分类器。在20Newsgroup、复旦中文分类语料、Reuters-21578三个语料集进行了比较实验,实验结果表明,新算法分类性能相对传统算法优势显著,且稳定、高效、实用,适于大规模文本分类任务。     

The generalized assortment and best cutting stock length problems

This paper introduces two new one-dimensional cutting stock models: the generalized assortment problem (GAP) and the best cutting stock length (BSL) problem. These new models provide the potential to reduce waste to values lower than the optimum of current models, under the right management circumstances. In the GAP, management has a standard length and can select one or more of any additional custom stock lengths, and management wishes to minimize cutting stock waste. This model is different from existing models that assume that the selection is from a small fixed set of stock lengths. In the BSL problem, management chooses any number of custom stock lengths, but wishes to find the fewest custom stock lengths in order to have zero waste. Results show waste reductions of 80% with just one custom stock length compared with solutions from standard cutting stock formulations, when item lengths are long relative to the stock length. The models are most effective when the item lengths are nearly as long as the stock length. Solutions from the model have been implemented for a manufacturer. The model is easily generalized to allow multiple existing stock lengths and different costs.     

基于ZigBee的智能环卫垃圾桶设计

在TI公司的CC2430芯片和ZigBee协议栈基础上,设计一种ZigBee技术的智能环卫垃圾桶。该原型由重量传感器、激光传感器、热红外感应器、语音芯片等组成。在电路设计方面,采用太阳能电池等绿色环保部件,使其更加符合绿色环保理念。城市环卫部门可通过ZigBee无线网络方便快捷的实时监控城市垃圾环卫信息,及时对垃圾进行清理,确保环境卫生,极大的方便了城市垃圾的管理。     

A GPS/GIS method for travel mode detection in New York City

Handheld GPS provides a new technology to trace people’s daily travels and has been increasingly used for household travel surveys in major cities worldwide. However, methodologies have not been developed to successfully manage the enormous amount of data generated by GPS, especially in a complex urban environment such as New York City where urban canyon effects are significant and transportation networks are complicated. We develop a GIS algorithm that automatically processes the data from GPS-based travel surveys and detects five travel modes (walk, car, bus, subway, and commuter rail) from a multimodal transportation network in New York City. The mode detection results from the GIS algorithm are checked against the travel diaries from two small handheld GPS surveys. The combined success rate is a promising 82.6% (78.9% for one survey and 86.0% for another). Challenges we encountered in the mode detection process, ways we developed to meet these challenges, as well as possible future improvement to the GPS/GIS method are discussed in the paper, in order to provide a much-needed methodology to process GPS-based travel data for other cities.     

Reliability and performance enhancements for SSD RAID

NAND based solid state storage devices are almost ubiquitously used in safety-critical embedded devices, and recent advances have demonstrated RAID architectures specific to solid state storage devices resulting in increased data reliability, with architectural enhancements to solve the age convergence problem. However, these techniques require devices to be taken off-line while components are replaced—consequently these devices are of limited use in hard real time systems. There are further real time issues in that the conventional architectures ignore other characteristics of solid state devices such as garbage collection and meta data management. In this paper we investigate techniques that support the replacement of aged devices in the array in such a way that we provide continuous system reliability. We also improve the performance overhead of the reconstruction process using a novel data migration policy. The techniques are implemented and tested in a trace-driven simulator, and results demonstrate that average I/O response time is improved by up to 39% with improvement by up to 45% in its standard deviation, overheads in terms of device replacement time are negligible, and read performance is improved by an average of 8%.     

多参数的城市时空热点查询

城市时空热点指城市居民来往次数较多且交通流量较大的时空区域。确定城市时空热点在城市基础设施建设、交通规划、商铺选址、打击犯罪等公共服务领域有大量的应用。目前的热点检测通常是在收集到的全部出租车轨迹上，采用Getis-Ord统计学方法，把轨迹按照时空立方单元进行划分，计算所有轨迹数据覆盖下的热点单元，作为城市时空热点。由于积累的轨迹数量庞大且计算复杂，现有检测算法的重点放在了如何应对海量的数据上。但随着实际应用的扩展，很多需求下的热点检测不需要用到全部数据，适当的数据组织可以使热点检测变得高效。针对实际应用的需要，时空热点查询可以按照用户指定参数（地理范围、日期范围、城市热点大小和时间组织方式），计算时空区域的热度，返回TOP-K热度单元作为时空热点。针对不同的查询参数，时空热点查询需要处理的数据不同，小粒度三维网格索引的轨迹数据组织方法能够快速提取需要处理的轨迹数据。用纽约市出租车轨迹数据集在Spark集群进行查询实验，结果证明这样的索引方法和存储策略能够满足指定参数，并大幅减少查询响应时间。