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.     

A simulation-based scheduling system for real-time optimization and decision making support

This paper presents an industrial application of simulation-based optimization (SBO) in the scheduling and real-time rescheduling of a complex machining line in an automotive manufacturer in Sweden. Apart from generating schedules that are robust and adaptive, the scheduler must be able to carry out rescheduling in real time in order to cope with the system uncertainty effectively. A real-time scheduling system is therefore needed to support not only the work of the production planner but also the operators on the shop floor by re-generating feasible schedules when required. This paper describes such a real-time scheduling system, which is in essence a SBO system integrated with the shop floor database system. The scheduling system, called OPTIMISE scheduling system (OSS), uses real-time data from the production line and sends back expert suggestions directly to the operators through Personal Digital Assistants (PDAs). The user interface helps in generating new schedules and enables the users to easily monitor the production progress through visualization of production status and allows them to forecast and display target performance measures. Initial results from this industrial application have shown that such a novel scheduling system can help both in improving the line throughput efficiently and simultaneously supporting real-time decision making.     

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.     

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.     

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 decision support system for paper making based on simulation and optimization

In this paper a model-driven decision support system related to paper making is introduced. The intention is to emphasize the necessity of coupling different modeling techniques, multiobjective optimization, and software engineering in order to make the end user application realistic, practical and usable. Firstly the paper making process and selected aspects concerning its mathematical modeling, numerical simulation, and multiobjective optimization are introduced, then the related computerized system, called a virtual paper making line, is described. In addition, the associated decision support system, which provides a suitable level of automation to improve the quality of decision making and support the user’s expertise is discussed. Finally, an example presents different ways of using such a software tool.     

A framework for applying ethics-by-design to decision support systems for emergency management

The development and utilisation of new information and communication technologies presents opportunities and risks, which bring ethical issues to the forefront. Any attempt to minimise the potential negative consequences to individuals, organisations and society resulting from the use of these technologies is challenging. In order to address these challenges, this paper presents an ethics-by-design approach that has been developed and implemented in the context of Decision Supports Systems for Emergency Management. Such systems help manage large and cross-border disasters by supporting decision makers to respond on emergencies in a reasonable way by taking follow-up actions into account. The approach taken in this paper specifically provides means to support the ethical dimensions of these decisions. Actions taken during disasters can have ramifications that persist long after a disaster has passed. The ethics-by-design approach presented here not only informs the design of systems, but also considers the role and training of the decision makers in the design process. The paper builds on the literature on ethics in information systems and makes a contribution to theory by providing a framework to ensure ethical considerations are embedded into the design of systems.     

Soft computing for crisis management and political decision making: the use of genetically evolved fuzzy cognitive maps

This paper examines the use of fuzzy cognitive maps (FCMs) as a technique for modeling political and strategic issues situations and supporting the decision-making process in view of an imminent crisis. Its object domain is soft computing using as its basic elements different methods from the areas of fuzzy logic, cognitive maps, neural networks and genetic algorithms. FCMs, more specifically, use notions borrowed from artificial intelligence and combine characteristics of both fuzzy logic and neural networks, in the form of dynamic models that describe a given political setting. The present work proposes the use of the genetically evolved certainty neuron fuzzy cognitive map (GECNFCM) as an extension of certainty neuron fuzzy cognitive maps (CNFCMs) aiming at overcoming the main weaknesses of the latter, namely the recalculation of the weights corresponding to each concept every time a new strategy is adopted. This novel technique combines CNFCMs with genetic algorithms (GAs), the advantage of which lies with their ability to offer the optimal solution without a problem-solving strategy, once the requirements are defined. Using a multiple scenario analysis we demonstrate the value of such a hybrid technique in the context of a model that reflects the political and strategic complexity of the Cyprus issue, as well as the uncertainties involved in it. The issue has been treated on a purely technical level, with distances carefully kept concerning all sides involved in it.     

考虑负效应的垃圾回收两级选址-路径模型与算法

针对生活垃圾中转站和焚烧站的选址-路径问题（LRP）,考虑经济目标和垃圾设施的负面影响,设计了与风向和距离有关的负效应分段函数,构建了两级多目标选址-路径（2E-MOLRP）模型,并提出了鲸鱼优化算法（WOA）和模拟退火（SA）算法结合的非支配算法WOA-SA。首先,结合随机方法与Clarke和Wright(CW)节约算法优化初始种群;其次,采用非线性动态惯性权重系数调整收敛速度;然后,设计WOA-SA的并行结构来增强全局搜索能力;最后,使用非支配排序法得到帕累托解集。对Prins和Barreto等35个基准案例以及天津市模拟案例进行分析。结果表明,WOA-SA可以找到20个基准案例的已知最优解（BKS）,且对Prins和Barreto案例的求解结果与BSK差距的平均值分别为0.37%和0.08%,具有很好的收敛性和稳定性。将所提模型和算法应用于实例,给决策者提供了三种不同方案的负效应值及经济成本的方案,以支持不同偏好决策者选择,从而减少垃圾回收物流成本和设施对环境的负面影响。     

Optimal capacity management and planning in services delivery centers

This paper considers human server systems of queues that arise within the information technology services industry. We develop a two-phase stochastic optimization solution approach to effectively and efficiently address the capacity management and planning processes of information technology services delivery centers. A large collection of numerical experiments of real-world human server system environments investigates various issues of both theoretical and practical interest, quantifying the significant benefits of our approach as well as evaluating the financial-performance trade-offs often encountered in practice.     

Approximate performance modeling and decision making for manufacturing systems: A queueing network optimization framework

In this paper we discuss queueing network methodology as a framework to address issues that arise in the design and planning of discrete manufacturing systems. Our review focuses on three aspects: modeling of manufacturing facilities, performance evaluation and optimization with queueing networks. We describe both open and closed network models and present several examples from the literature illustrating applications of the methodology. We also provide a brief outline of outstanding research issues. The paper is directed towards the practitioner with operations research background and the operations management researcher with interest in this topic.     

Software project management using PROMPT: A hybrid metrics, modeling and utility framework

In this paper, we present a ‘forward-looking’ decision support framework that integrates up-to-date metrics data with simulation models of the software development process in order to support the software project management control function. This forward-looking approach (called the PROMPT method) provides predictions of project performance and the impact of various management decisions. Tradeoffs among performance measures are accomplished using outcome based control limits (OBCLs) and are augmented using multi-criteria utility functions and financial measures of performance to evaluate various process alternatives. The decision support framework enables the program manager to plan, manage and track current software development activities in the short term and to take corrective action as necessary to bring the project back on track. The model provides insight on potential performance impacts of the proposed corrective actions. A real world example utilizing a software process simulation model is presented.     

《固体废弃物处理与处置》多媒体课件开发

《固体废弃物处理与处置》是环境工程学科的一门核心课程，不但概念公式繁多，而且还有大量的实物图例以及工艺流程图。本文以Macromedia Authorware 5．0为开发工具，开发了《固体废弃物处理与处置》多媒体CAI课件。本文对课件的框架结构作了介绍，着重阐述了概念表述、公式推导、工艺流程等主要教学内容的图象表现方式和动态交互式表现方式，使复杂内容简单化、静态内容动态化，具有较好的教学效果。     

Participatory Framework for Assessment and Improvement of Tools (ParFAIT): Increasing the impact and relevance of water management decision support research

This paper proposes the Participatory Framework for Assessment and Improvement of Tools (ParFAIT) as a way to address low uptake of Water Resources Systems Optimization (WRSO) tools. ParFAIT is a transdisciplinary process conducted in five stages, two of which are participatory modeling (PM) exercises. Herein we describe the framework, introduce our candidate tool- Multiobjective Evolutionary Algorithm (MOEA)-assisted optimization, and present the results of our first PM workshop. MOEA-assisted optimization has been put forth as a planning and decision making aid for utilities facing a large number of decisions and highly uncertain futures. The PM workshop, designed to solicit input on a tool testbed, was held in February 2015 with representatives from six Front Range, Colorado, water utilities. Our results include an expanded characterization of the decision making landscape, feedback on water utility decisions and performance goals commonly employed in WRSO studies, and new questions that warrant future investigation by researchers.     

Agent-based negotiation and decision making for dynamic supply chain formation

Modern businesses are facing the challenge of effectively coordinating their supply chains from upstream to downstream services. It is a complex problem to search, schedule, and coordinate a set of services from a large number of service resources under various constraints and uncertainties. Existing approaches to this problem have relied on complete information regarding service requirements and resources, without adequately addressing the dynamics and uncertainties of the environments. The real-world situations are complicated as a result of ambiguity in the requirements of the services, the uncertainty of solutions from service providers, and the interdependencies among the services to be composed. This paper investigates the complexity of supply chain formation and proposes an agent-mediated coordination approach. Each agent works as a broker for each service type, dedicated to selecting solutions for each service as well as interacting with other agents in refining the decision making to achieve compatibility among the solutions. The coordination among agents concerns decision making at strategic, tactical, and operational level. At the strategic level, agents communicate and negotiate for supply chain formation; at the tactical level, argumentation is used by agents to communicate and understand the preferences and constraints of each other; at the operational level, different strategies are used for selecting the preferences. Based on this approach, a prototype has been implemented with simulated experiments highlighting the effectiveness of the approach.     

On the formulation of cost functions for torque-optimized control of rigid bodies

In the context of controlling the attitude of a rigid body, this communique uses recent results on representations of torques (moments) to establish cost functions. The resulting cost functions are both properly invariant under whatever choice of Euler angles is used to parameterize the rotation of the rigid body and have transparent physical interpretations. The function is related to existing works in geometric control theory and applications of optimal control theory to biomechanical systems.     

A knowledge-based decision support system for the management of parts and tools in FMS

Flexible manufacturing systems (FMS) are very complex systems with large part, tool, and information flows. The aim of this work is to develop a knowledge-based decision support system (KBDSS) for short-term scheduling in FMS strongly influenced by the tool management concept to provide a significant operational control tool for a wide range of machining cells, where a high level of flexibility is demanded, with benefits of more efficient cell utilization, greater tool flow control, and a dependable way of rapidly adjusting short-term production requirements. Development of a knowledge-based system to support the decision making process is justified by the inability of decision makers to diagnose efficiently many of the malfunctions that arise at machine, cell, and entire system levels during manufacturing. In this context, this paper proposes three knowledge-based models to ease the decision making process: an expert production scheduling system, a knowledge-based tool management decision support systems, and a tool management fault diagnosis system. The entire system has been created in a hierarchical manner and comprises more than 400 rules. The expert system (ES) was implemented in a commercial expert system shell, Knowledge Engineering System (KES) Production System (PS).     

两种固体氧化物燃料电池系统的故障建模与仿真对比研究

固体氧化物燃料电池(SOFC)系统的建模方式较多,而基于机理模型的故障诊断是能够通过系统的动态趋势辨别故障的有效手段之一,但该方法对机理模型的准确性有要求.此外,不同的燃料供给系统采用的系统结构也是有差异的,进而导致在相同故障下SOFC系统的动态响应也是不同的.因此,本文基于两种燃料供应方式,提出了分别以纯氢气和天然气作为燃料的SOFC系统结构,并基于原有机理知识进行MATLAB/Simulink系统建模.经与真实SOFC系统实验对比,搭建的系统模型能够有效模拟系统在无故障状态下的动态变化;另外,在无故障模型的基础上,分别加入两类常见故障,其一为风机故障,其二为燃料供应管路泄露.最后通过仿真分析,明确了所搭建模型的合理性,且发现了两种燃料供应对SOFC系统热响应特性是不同的,对SOFC系统故障的检测和设备选型具有重要意义.     

A survey of reasoning procedures in knowledge based systems for economics and management

This paper surveys reasoning and inference strategies as especially relevant for knowledge based systems in economics and management. This requires elements of object oriented features, numerical and text constraints, search over time, game power conflict resolution. Specific functionalities are discussed.